{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 《python数据可视化之matplotlib实践》\n",
    "## chapter-1 \n",
    "![overview](overview.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " Volume in drive E is Files\n",
      " Volume Serial Number is BA96-2D6A\n",
      "\n",
      " Directory of E:\\pycharm\\可视化\n",
      "\n",
      "12/26/2019  11:15 PM    <DIR>          .\n",
      "12/26/2019  11:15 PM    <DIR>          ..\n",
      "12/26/2019  08:34 PM    <DIR>          .ipynb_checkpoints\n",
      "12/26/2019  03:27 PM             2,851 chapter-1 - demo.py\n",
      "12/26/2019  03:14 PM             2,993 chapter-1.py\n",
      "12/26/2019  08:29 PM             2,351 chapter-2.py\n",
      "12/26/2019  10:36 PM             4,460 chapter-3.py\n",
      "12/26/2019  03:28 PM           326,446 matplotlib可视化学习-chapter-1.ipynb\n",
      "12/26/2019  10:08 PM           281,731 matplotlib可视化学习-chapter-2.ipynb\n",
      "12/26/2019  11:15 PM           176,829 matplotlib可视化学习-chapter-3.ipynb\n",
      "12/26/2019  01:15 PM           475,527 overview.png\n",
      "               8 File(s)      1,273,188 bytes\n",
      "               3 Dir(s)  33,152,094,208 bytes free\n"
     ]
    }
   ],
   "source": [
    "!dir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## line"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "\"\\nmatplotlib.iines.Line2D.set_linestyle\\n\\nlinestyle\\t\\tdescription\\n'-'or 'solid' \\tsolid line\\n'--'or'dashed'\\tdashed line\\n'-.'or'dash_dot'\\tdash-dotted line\\n':'or'dotted'\\tdotted line\\n'None'\\t\\tdraw nothing\\n' '\\t\\t\\tdraw nothing\\n''\\t\\t\\tdraw nothing\\n\""
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "x = np.linspace(0.5, 3.5, 100) # Returns num evenly spaced samples, calculated over the interval [start, stop].\n",
    "y = np.sin(x)\n",
    "\n",
    "plt.plot(x, y, \n",
    "\tls='-.', # 折线图的线条风格\n",
    " \tlw=2,   # 折线图的线宽\n",
    " \tlabel='plot figure')\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "'''\n",
    "matplotlib.iines.Line2D.set_linestyle\n",
    "\n",
    "linestyle\t\tdescription\n",
    "'-'or 'solid' \tsolid line\n",
    "'--'or'dashed'\tdashed line\n",
    "'-.'or'dash_dot'\tdash-dotted line\n",
    "':'or'dotted'\tdotted line\n",
    "'None'\t\tdraw nothing\n",
    "' '\t\t\tdraw nothing\n",
    "''\t\t\tdraw nothing\n",
    "'''\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX8AAAD8CAYAAACfF6SlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAIABJREFUeJzt3Xl4VdW9//H3NzNDmJIAkYRBZkTGw+AIXCccLmi1glNxKop6O6nV2l5t7X2svfqz1jqVVqu1FkUrlku14oAgyhRkkEEGGcOUMGRgyLx+fySGJCQk5Jxkn+Hzeh4ezt57nbO+K/uc71ln7b3XNuccIiISWaK8DkBERJqfkr+ISARS8hcRiUBK/iIiEUjJX0QkAin5i4hEICV/EZEIpOQvIhKBlPxFRCJQjNcB1CU5Odl1797d6zBERELK8uXL9zvnUuorF7TJv3v37mRkZHgdhohISDGz7Q0pp2EfEZEIpOQvIhKBlPxFRCJQ0I75i0h4KC4uJjMzk4KCAq9DCSsJCQmkpaURGxvbqOcr+YtIk8rMzCQxMZHu3btjZl6HExaccxw4cIDMzEx69OjRqNcIyLCPmb1sZllmtqaO7WZmz5jZZjNbbWbDAlGviAS/goICkpKSlPgDyMxISkry69dUoMb8XwHGn2T7pUDvin9TgRcCVK+IhAAl/sDz928akOTvnFsAHDxJkYnAX125xUA7M0sNRN0S3HKOFrFqZw5Zecd7KKt25nDP37/k2U82VSt700tLuOmlJRwrKq1cN29DFm8u28HOg0ebLWaRSNBcZ/t0AXZWWc6sWFeNmU01swwzy8jOzm6m0CRQVu7M4ZXPt1ZL3o+//zUTn/ucD9btq1yXV1DMnNV7WLK1en/hi28O8Nmm/cTFHH9b/n3JDh74x1es3Z1XuW7BxmymvLyUmRk7EfHH2LFj672Y9LHHHqtz21tvvUX//v0ZN24cGRkZ/OAHPwh0iE2muQ741vb75IQ7xzvnpgPTAXw+n+4sH8SOFJawKeswQ9LbVa77ycyVbMk+wvBuHTgzrS0AvTslMiC1DS1ioyvL9U9tw+8nDyG1bYtqr/narSMpdY7oqONvl/P7pNC2RSw9U1pVrvtyxyHmb8ymX+fEynX7Dxfy4D++4vw+yXzvrO6Bbq5EsMcee4yHHnqo1m0vvfQSzz//POPGjQPA5/MFpM6SkhJiYpo2PTdXzz8TSK+ynAbsbqa6JcByjhYx9NEPmfTHRRSWHO/lXzYwle8OT6NF3PFEf9u5PXjvh+dxzfC0ynXJreOZOKQLI3t0qPa6Z/dK5rze1ackuWl0N5787mB6dzqe6CeP6MoLNwxj4pDjPx6/3H6Ij9bv41+r91R7/heb91f7JSKRZ9u2bfTr148pU6YwaNAgrrnmGo4ePXEYccaMGZx55pkMHDiQBx54AIAHH3yQY8eOMWTIEG644YZq5R999FEWLlzInXfeyf3338+nn37KFVdcAUB2djYXXXQRw4YN44477qBbt27s37+fbdu2MXDgwMrXePLJJ/nlL38JlP8KeeihhxgzZgy///3vyc7O5uqrr2bEiBGMGDGCzz//PLB/GOdcQP4B3YE1dWy7HHif8l8Ao4Gl9b3e8OHDnXgv52iRe/HTze6Rf66ptn7CHz5zE55d6HYcOOJRZNVl5RW4tzN2urlr91au25NzzHV7YI4b8qsPXHFJqYfRRbZ169ZVW+72wBzX7YE51dbd+pelrtsDc9yHVfbf64u3u24PzHEP/mNV5bq9ueX7dMT/fNjg+rdu3eoAt3DhQuecc7fccot74oknnHPOjRkzxi1btszt2rXLpaenu6ysLFdcXOzGjRvnZs2a5ZxzrlWrVnW+9rfPd865efPmucsvv9w559zdd9/tHnvsMeecc++//74DXHZ2ttu6das744wzKp//xBNPuEceeaTytaZNm1a57brrrnOfffaZc8657du3u379+p1Qf82/rXPOARmuATk7IL8rzGwGMBZINrNM4BEgtuLL5UXgPeAyYDNwFLglEPVK03DOHT+TwMGTczdQWua45z96kdw6HoC3p51NbHTwXCCekhjP1VV+XUD5UNDg9HZ0bhNPTEWszjme+nAjF/TvxOC0tjoLJUKkp6dzzjnnAHDjjTfyzDPPcN9991VuX7ZsGWPHjiUlpfyX5w033MCCBQu48sorG1XfwoULmTVrFgDjx4+nffv2DXrepEmTKh9/9NFHrFu3rnI5Ly+P/Px8EhMTa3vqKQtI8nfOXVfPdgfcHYi6pOkcOlLE7z/exMZ9+fz9+6MBaNsylnsv7kv3pFYkJhx/uwRT4q/LwC5t+efd51BcWla5bt2ePP7wyWZeW7ydJQ9dQHxM9EleQZrCtscvP2HdSzePOGHd9aO6cv2ortXWdWqTUOvz61PzS77mcnmKCpy6Xi8mJoaysuPvx5rn6bdqdfzYVllZGYsWLaJFi+rHxgIl+D/B0mwSYqN558tMvvjmAN9kH65cf+eYnowf2DlkE2XVL6oOreL4/nk9uOXsHpXtKStzPPvJJnblHPMqRGliO3bsYNGiRUD52P65555bbfuoUaOYP38++/fvp7S0lBkzZjBmzBgAYmNjKS4uPqX6zj33XGbOnAnA3LlzOXToEACdOnUiKyuLAwcOUFhYyJw5c+p8jYsvvphnn322cnnlypWnFEN9lPwjVGmZY/aq3dz9+peUlZX3UlrERfP41YN47wfn0TOltccRNo3Uti34+eUD+OGFvSvXffJ1Fk/O3cjk6Ysq/xYSXvr378+rr77KoEGDOHjwINOmTau2PTU1ld/85jeMGzeOwYMHM2zYMCZOnAjA1KlTGTRo0AkHfE/mkUceYe7cuQwbNoz333+f1NRUEhMTiY2N5eGHH2bUqFFcccUV9OvXr87XeOaZZ8jIyGDQoEEMGDCAF198sXGNr4MF+udOoPh8PqebuTSdwpJSxj3xKbtzC/jjTcO55IzOXofkmQ1783lu3mZGdG/PTRWniRaXlrH9wFF6dQzPL8HmtH79evr37+9Z/du2beOKK65gzZpaZ59pEoWFhURHRxMTE8OiRYuYNm1awHvuUPvf1syWO+fqPedUE7tFCOccn3ydxfl9UoiNjiI+JpqHLu9P7rFixvSp945vYa1v50SeuW5otXVvL8/k57O+4u5xvbj34r4eRSahaseOHVx77bWUlZURFxfHn/70J69DOoGSf4S4d+Yq3lmxi19PPKOyd3vFoNO8DSqI7csrIMqs2vUFEpq6d+/erL1+gN69e7NixYpmrfNUKflHiIvP6MT8jdm0jNMub4gfXdiHa4ancVqVq5BnLN3BkcISppzdPSTOdgom1U4floDwd8hemSAMFRSX8sf5W2jXMpYpZ3cH4JIzOnNe7xRaxWuXN1Ra+5aVj/MKinn8/a/JPVZMz46tGde3o4eRhZaEhAQOHDigaZ0DyFXM55+QkNDo11AmCEOLthzgdx9tpHV8DFcN60KbhFjMTInfD4nxMTx17WDmbchibJVjJCWlZZUXkEnt0tLSyMzMRJM1Bta3d/JqLGWDMFE1CY3r25E7xpzOuL4daZPQuFu8SXVmxgX9O3FB/06V67LyCvjOC19wz7heTBqRrl5tHWJjYxt9tylpOuqyhDjnys/XH/vkp+yucpHSzy7tz+jTkzyMLPy9/WUmmYeO8cHavV6HInLK1PMPA7NX7ibz0DFmZuzkRxf28TqciDFtTE+6tGuBr3uHyl7/saJS4mOiiIrSrwAJbkr+IerbYR4z47GrBnLRgI5c60uv/4kSMGZWbVppgJ/+YzWHjhTxxHcHnXC/ApFgouQfYo4UlvDrOevIOVrMCzcOw8zo2CaBSSO61v9kaVL78gpYuCmbwpIyCorL6n+CiIeU/EPMwSNFzFm9h6LSMjZnHdZFSEGkU5sE5v54DF/vzaNH8vHZGYtLy3RdgAQdJf8Qk96hJU9PGkJahxZK/EEoJTGelMTjp4LO25DFY/9az3M3DKOP9pcEEXVHglxeQTF3vb6cj6rcAP3CAZ3o17mNh1FJQ02fv4VNWYf5sMr+EwkG6vkHuXdX7OK9r/by1a5cxvZN0QVFIealm328vngHt52r89wluCiTBLkbR3Vj6vmn89qto5T4Q1DLuBi+f/7plad+Hi4s4cdvrqx2TYaIF5RNgkxpmWP6gm84XFgCQFSU8dBl/ele5QCihK4n/v01s1bs4iczAz+3u8ip0LBPkPn1nHW88sU2VuzI4YUbh3sdjgTYjy7sQ1Z+IfdfonsEiLcC0vM3s/FmtsHMNpvZg7Vs72pm88xshZmtNrPLAlFvOJpydnd6JLfiexVz7kt4ad8qjhduHM7pVW6T+dmmbEpKdV2ANC+/k7+ZRQPPAZcCA4DrzGxAjWK/AGY654YCk4Hn/a03nOzLK6h83CO5FR/9ZAxn9dS8PJFg7tq9fO/lpdzyyjJKdf9gaUaB6PmPBDY757Y454qAN4CJNco44NtzE9sCuwNQb1j4x/JMzvvfefx7zfHJwaI1L0zESGodR1KrOEafnqT9Ls0qEGP+XYCdVZYzgVE1yvwSmGtm/wW0Ai4MQL1hYV9+AUUlZazKzGH8wMi9iXqkGt6tA//+0fkktYqrXKe7XklzCETPv7Z3ac3fr9cBrzjn0oDLgNfM7IS6zWyqmWWYWUak3Phh2pievH77KB4Y38/rUMQjya3jK5N97tFirnr+Cz7dkOVxVBLuApH8M4Gq00mmceKwzm3ATADn3CIgAUiu+ULOuenOOZ9zzpeSklJzc1g4WlTCL2evJfdYMVA+M+Q5vU74U0iEmrFsByt35vDbf2/QMQBpUoEY9lkG9DazHsAuyg/oXl+jzA7gAuAVM+tPefKPjK59DT+ftYZZK3axL69Ap3LKCe44/3RKyxxXDe2iYwDSpPzu+TvnSoB7gA+A9ZSf1bPWzB41swkVxe4Fvm9mq4AZwM3O31vPh6h7L+6Dr1t77tN53lILM+Pucb04rd3xewEs3XqQCP24SBOyYH1T+Xw+l5GR4XUYAXG0qISWccd/ZOmAnjTUWxk7uf/t1Vw3Mp3HrjpT7xupl5ktd8756iun6R2a2Ia9+Yx78lNmrcisXKcPsDRUcut4EmKj6NUxUe8bCSgl/yb2+eb97Msr5J0vd+mnu5yycf068vG9YzUrqASc5vZpYree24MOreIYP7Czem7SKF2qjP8fPFLE7z7cyEOX9adFXLSHUUmoU8+/CazcmUPu0eLK5SuHdiEhVh9U8d+P31zJa4u388jsNV6HIiFOyT/AMrYd5Po/Leaml5dUTsssEigP/+cAzumVxH0X62wx8Y+GfQLstHYtSG4dT6+OrWmh3r4EWM+U1rx+++hq60rLnK4JkFOm5B9gp7VrwTt3nU37lnH6QEqTe33Jdt5dsYu/3DKS1vH6OEvDadgnADK2Hax2Kmdy63glfmlyR4tKeH7eNyzbdohPvtZcQHJq1FXw097cAm7+yzKOFJXQuU0LzcMvzaZlXAx///4oFn1zgAmDT/M6HAkxSv5+6tw2gWlje7JxXz4je3TwOhyJMN2SWtEt6fj9nXOOFtEiLpr4GB1vkpNT8g+Au8f10pQN4rn9hwu58c9L6JbUkueuH0ZMtEZ1pW56dzTC9gNH+P5fM8g5WlS5TolfvJadX8iunGNszjpMzrHi+p8gEU3JvxEe+MdqPly3jyfnbvA6FJFK/VPb8Prto3jzjrNIbh3vdTgS5JT8G+F3k4bwnaFdePDS/l6HIlLNoLR21RL/2t25HkYjwUzJv4GqTsqW2rYFT00aovOqJai9vHArlz+zkJcXbvU6FAlCSv4NUFRSxs1/WcbMjJ31FxYJEm1axGIGZZpNVmqhrmsDfLhuH/M3ZrN2dx6XDuxMYkKs1yGJ1Oua4WkMSW9Lr46JXociQUjJvwEuH5TKwaMDGZreTolfQkrVxH/oSBG7c49xxmltPYxIgoWS/0mUlJZVnit90+huHkcj0nhZ+QVMnr6YQ0eKeHva2fRMae11SOIxjfnX4d0Vu7j6xUVk5xd6HYqI39q3jKNrh5Z0apOgExUECFDyN7PxZrbBzDab2YN1lLnWzNaZ2Voz+3sg6m0qxaVl/OGTTazamcPH6/d5HY6I32Kjo3j+hmHMvPMsOrVJ8DocCQJ+dwHMLBp4DrgIyASWmdls59y6KmV6Az8DznHOHTKzjv7W25Rio6N4Y+pZzFm9m8kju3odjkhAtIyr/nGfvzGbc3omaRqICBWIvT4S2Oyc2+KcKwLeACbWKPN94Dnn3CEA51xQzj9bUlpW+TglMZ5bztFNsyU8TV/wDVNeXsp//3NttWtYJHIEIvl3AaqeAJ9Zsa6qPkAfM/vczBab2fgA1BtQhwtLuOr5L/jrom1ehyLS5IZ360DLuGgGpCZqXqoIFYgjP7W9c2p2JWKA3sBYIA34zMwGOudyqr2Q2VRgKkDXrs073PLx+n18tSuX/IJirhmedsJPZJFwMrxbexb8dJzmAIpggchwmUB6leU0YHctZRY754qBrWa2gfIvg2VVCznnpgPTAXw+X7P+Fp04pAvOweD0dkr8EhGqJv79hwvZm1vAwC66BiBSBGLYZxnQ28x6mFkcMBmYXaPMu8A4ADNLpnwYaEsA6vZbWdnx75grh3ahR3Krk5QWCT+7c45x5XOfc/NflrLz4FGvw5Fm4nfyd86VAPcAHwDrgZnOubVm9qiZTago9gFwwMzWAfOA+51zB/yt21/zNmQx4bmF7M455nUoIp5JSYynR3IrurRrQXyMzvyJFBasR/p9Pp/LyMhostcvK3Nc+fznrM7M5YHx/Zg2tmeT1SUS7PILiomNjiIhVrd/DHVmttw556uvXMR+zUdFGX+9dST3X9KXO84/3etwRDyVmBBbLfF/ueOQh9FIc4i45F/1l067lnHcPa4XUVE61U3kW7/999d85/kvmLF0h9ehSBOKqOTvnOOhWV8xfcE3urBFpA49klsRG22oTxTeIuqcxlWZucxYupP4mCjGn5FK16SWXockEnSu9aVz1ulJpHfQ5yOcRVTyH5LejhduGEapc0r8IidRNfFn5RfQKi6GVpoNNKxE3N689MxUr0MQCRlrduVy+6sZDElvx/M3DNPxsTAS9mP+hwtLuPvvX7L9wBGvQxEJOS3iojlSVML+w4UcKSrxOhwJoLDv+T81dyP/Wr2HrLwCZt5xliaxEjkFPVNa8+bUs+jVsTVxugAsrIR98v/xRb05eKSQH17YR4lfpBEGnNam2nJeQTFtdC/rkBf2X+WJCbE8PXmo5uwR8VNRSRk/n/UVVz77OXkFxV6HI34Ky+S/JfswL87XufwigVRSVsby7YfIzDnG6p25Xocjfgq7YZ+S0jKm/e1LNuzLJybKuP08Td0gEggt42L4403DyT1WzKC0dl6HI34Ku55/THQUPx3fl+Hd2uv+uyIB1i2pVbXEX3VKdAktYZf8AS7o34m37zyL1rooRaTJLN9+kEueXsCOA7oHQCgKy+QP6MwekSb20sKtbMo6zB8XfON1KNII6hqLSKP85juDGJDahjvG6F4YoUjJX0QapW2LWO75j95ehyGNFLbDPiLSfAqKS/nFu1+xameO16FIAyn5i4jfXv58K39bvIMfz1xJqc4ACgka9hERv912bg/W7c7jzjE9idbMnyEhID1/MxtvZhvMbLOZPXiScteYmTOzem8uLCKhIz4mmmevH8bALm29DkUayO/kb2bRwHPApcAA4DozG1BLuUTgB8ASf+sUkeC2dOtBFm854HUYchKB6PmPBDY757Y454qAN4CJtZT7NfC/QEEA6hSRILV060Gu+9Ni7vn7CrLzC70OR+oQiOTfBdhZZTmzYl0lMxsKpDvn5gSgPhEJYsO7tWdUjw5cPbwL7Vpq6udgFYgDvrUd3ak83G9mUcDvgJvrfSGzqcBUgK5dNS+PSCiKjjJevXUksdE6mTCYBWLvZALpVZbTgN1VlhOBgcCnZrYNGA3Mru2gr3NuunPO55zzpaSkBCA0EfFC1cRfUFzK+j15HkYjtQlE8l8G9DazHmYWB0wGZn+70TmX65xLds51d851BxYDE5xzGQGoW0SC2P7DhVz53Ofc8Ocl7M3V4b5g4nfyd86VAPcAHwDrgZnOubVm9qiZTfD39UUkdLVvGUdKYjxtEmJ0968gY8F6tyufz+cyMvTjQCTUHTxSRGy0kaj7/jYLM1vunKv3Wipd4SsiTapDq7hqy0eLSmgZp9TjNR2OF5FmUVbmeP7TzfzHk/N1/n8QUPIXkWbhgAUbs9mbV8C8r7O8Difi6beXiDSL6Cjj95OHsn5PHmP7dvQ6nIin5C8izaZTmwQ6tUnwOgxBwz4i4pEt2Ye5/dUMco/qFFAvKPmLiCf++59r+Gj9Pp76cIPXoUQkJX8R8cRvrhrEJF86913S1+tQIpLG/EXEE12TWvLbawZ5HUbEUs9fRDxXVuaYsXQHBcWlXocSMZT8RcRzD89ew8/e+Yr/+dc6r0OJGEr+IuK5ySO60rlNAuN0/n+z0Zi/iHhuYJe2zP/pWOJjor0OJWKo5y8iQaFq4t+Vc4zSsuCccThcKPmLSFD51+o9XPzUfF6c/43XoYQ1JX8RCSqt4qM5UlTKhr35BOv9RsKBxvxFJKiM7duRWXedzZD0dpiZ1+GELfX8RSToDO3avjLxq/ffNJT8RSRoZecXcusry5izerfXoYQdDfuISND6aP0+5m3I5pvsI4w/ozMx0eqvBoqSv4gErckj0tmbW8DkkelK/AEWkL+mmY03sw1mttnMHqxl+0/MbJ2ZrTazj82sWyDqFZHwZmb8+KI+pLZt4XUoYcfv5G9m0cBzwKXAAOA6MxtQo9gKwOecGwS8Dfyvv/WKSOT5v1W7WZ2Z43UYYSEQPf+RwGbn3BbnXBHwBjCxagHn3Dzn3NGKxcVAWgDqFZEI8u6KXfzXjBX86I2Vmv0zAAKR/LsAO6ssZ1asq8ttwPu1bTCzqWaWYWYZ2dnZAQhNRMLF+IGdGZzWllvP7UF8jMb//RWIA761XYVR64m5ZnYj4APG1LbdOTcdmA7g8/l0cq+IVEqIjWbWXecQFaULvwIhEMk/E0ivspwGnHBSrpldCPwcGOOcKwxAvSISYaom/kNHiih1juTW8R5GFLoC8dtpGdDbzHqYWRwwGZhdtYCZDQX+CExwzmUFoE4RiWArdhzikqcXcN9bq3QFcCP5nfydcyXAPcAHwHpgpnNurZk9amYTKoo9AbQG3jKzlWY2u46XExGpV2rbFhSWlHG4oIS8ghKvwwlJFqzfmj6fz2VkZHgdhogEqU378umR3EoXf9VgZsudc776yukKXxEJSb07JVZbds5pFtBToK9MEQlpR4tK+Nk7X/Hk3A1ehxJSlPxFJKSt35PPm8t28NLCrWTn60TChtKwj4iEtOHd2vOriQMZ0b09KYk67bOhlPxFJOTdNFpzRZ4qDfuISFhZuvUg877W5UT1UfIXkbCxfPshJk1fxE9mriQrv8DrcIKahn1EJGwM69qOsX1SOOO0trRrEed1OEFNyV9EwoaZ8ecpI4jW5G/10rCPiISVqom/oLiUvbka/qmNkr+IhKVt+48w4dmF3PFaBsWlZV6HE3SU/EUkLHVoHceRwlLyC0rI0sVfJ9CYv4iEpTYJsbxyywi6tG9Byzilupr0FxGRsFVz8jc5TsM+IhL2SkrLeObjTfxy9lqvQwkaSv4iEva2HTjCHz7ZxKuLtrE567DX4QQFDfuISNjr1TGRX00YSLeklvTq2NrrcIKCkr+IRITrR3X1OoSgomEfEYk4m7MOR/zkb0r+IhJRNmcd5vJnPuMHM1awK+eY1+F4JiDJ38zGm9kGM9tsZg/Wsj3ezN6s2L7EzLoHol4RkVPVM6UVY/qkcMnAziQmRO7It98tN7No4DngIiATWGZms51z66oUuw045JzrZWaTgd8Ck/ytW0TkVJkZz14/jLiYyB74CETrRwKbnXNbnHNFwBvAxBplJgKvVjx+G7jAzDTtnoh4omriLytz7D8cedM/BCL5dwF2VlnOrFhXaxnnXAmQCyQFoG4RkUbLyi/ghj8v4aaXllJUElmTvwUi+dfWg3eNKIOZTTWzDDPLyM7ODkBoIiJ1axkXQ2bOUbLzC9h24IjX4TSrQBztyATSqyynAbvrKJNpZjFAW+BgzRdyzk0HpgP4fL4TvhxERAKpdXwM02/y0TExnqTW8V6H06wC0fNfBvQ2sx5mFgdMBmbXKDMbmFLx+BrgE+eckruIeK5/apuIS/wQgORfMYZ/D/ABsB6Y6Zxba2aPmtmEimIvAUlmthn4CXDC6aAiIl5yzjEzYye/nrOu/sJhICAnuTrn3gPeq7Hu4SqPC4DvBqIuEZGmkHnoGL94dw1FJWX85+DTGJLezuuQmlTkXuEgIlJFeoeWPHzFAFrGRTM4ra3X4TQ5JX8RkQo3ju7mdQjNJrIvcRMRqUNWfgELNobvKedK/iIiNezJPcb4pz9j2t+Ws/PgUa/DaRIa9hERqaFzmwRGn96B/IISYqPDs4+s5C8iUoOZ8eR3B5MQE01UVHhOQxaeX2kiIn5qGRdTLfHnFRR7GE3gKfmLiJxEfkExP3xjBde88AUFxaVehxMwSv4iIicRHWV8lZnLzoPHWLs71+twAkZj/iIiJ9EyLoZnrx9GQmwUp6e09jqcgFHyFxGpx4DT2ngdQsBp2EdE5BTM35jNo/8X+pO/qecvItJAh44UcdfflnOkqJTz+yQztm9Hr0NqNCV/EZEGat8qjof/cwD7DxdxXu8Ur8Pxi5K/iMgpmDSiq9chBITG/EVEGulIYQmfbQrNyd+U/EVEGiG/oJjLn/mM217J4Ou9eV6Hc8qU/EVEGiExIZazeiZxekoroi305v/RmL+ISCM9fMUZREVBfEy016GcMvX8RUQaqUVcdLXEf6SwxMNoTo1fyd/MOpjZh2a2qeL/9rWUGWJmi8xsrZmtNrNJ/tQpIhJsikvLePz9r7noqfnkHC3yOpwG8bfn/yDwsXOuN/BxxXJNR4HvOefOAMYDT5tZOz/rFREJGgYs3XqAvXkFfL75gNc7Eu1LAAAH0ElEQVThNIi/Y/4TgbEVj18FPgUeqFrAObexyuPdZpYFpAA5ftYtIhIUYqKjeHrSULLyC/B17+B1OA3ib/Lv5JzbA+Cc22NmJ73W2cxGAnHAN37WKyISVLomtaRrUkuvw2iweod9zOwjM1tTy7+Jp1KRmaUCrwG3OOfK6igz1cwyzCwjOzs0L5wQEVm7O5f73lpFSWmtqS4o1Nvzd85dWNc2M9tnZqkVvf5UIKuOcm2AfwG/cM4tPkld04HpAD6fz9UXm4hIsCkpLWPa375kx8GjDEhtw63n9vA6pFr5e8B3NjCl4vEU4J81C5hZHDAL+Ktz7i0/6xMRCWox0VE8/p0zuWl0N64bGbzzAPk75v84MNPMbgN2AN8FMDMfcKdz7nbgWuB8IMnMbq543s3OuZV+1i0iEpTO7pXM2b2SvQ7jpMy54Bxd8fl8LiMjw+swRET8UlJaxkfr9zF+YGqz1Gdmy51zvvrK6QpfEZEm4pxjyl+WcuffvuSfK3d5HU41Sv4iIk3EzLjszFQ6t0mgU5sEr8OpRhO7iYg0oetHdmXC4NNITIj1OpRq1PMXEWlCZlYt8QfL3D9K/iIizeS1xds5+/FPyNh20OtQlPxFRJpL5qGjHC0qZcFG72cw0Ji/iEgzufeivpx1ehJj+550GrRmoZ6/iEgziYuJCorED0r+IiKe2J1zjCkvL+Wb7MOe1K/kLyLigWfnbWb+xmz+Z846T+rXmL+IiAd+dmk/AO69qI8n9Sv5i4h4IDEhlseuOtOz+jXsIyLiMeccbyzdwd7cgmarU8lfRMRjL87fwoPvfMWP3lxBWVnzzLSs5C8i4rFrhqfRI7kV143sSlSUNUudGvMXEfFYSmI8H/74fGKim68/rp6/iEgQaM7ED0r+IiIRSclfRCQCKfmLiEQgv5K/mXUwsw/NbFPF/+1PUraNme0ys2f9qVNERPznb8//QeBj51xv4OOK5br8GpjvZ30iIhIA/ib/icCrFY9fBa6srZCZDQc6AXP9rE9ERALA3+TfyTm3B6Di/xMmqjazKOD/Aff7WZeIiARIvRd5mdlHQOdaNv28gXXcBbznnNtpdvIr18xsKjAVoGvXrg18eREROVX1Jn/n3IV1bTOzfWaW6pzbY2apQFYtxc4CzjOzu4DWQJyZHXbOnXB8wDk3HZgO4PP5mmeCCxGRCOTv9A6zgSnA4xX//7NmAefcDd8+NrObAV9tiV9ERJqPOdf4DraZJQEzga7ADuC7zrmDZuYD7nTO3V6j/M2UJ/97GvDa2cD2RgcHycB+P54fLMKlHaC2BKtwaUu4tAP8a0s351xKfYX8Sv7BzMwynHM+r+PwV7i0A9SWYBUubQmXdkDztEVX+IqIRCAlfxGRCBTOyX+61wEESLi0A9SWYBUubQmXdkAztCVsx/xFRKRu4dzzFxGROoR08jez8Wa2wcw2m9kJ1w6Y2c1mlm1mKyv+3V7b6wQDM3vZzLLMbE0d283Mnqlo62ozG9bcMTZEA9ox1sxyq+yTh5s7xoYys3Qzm2dm681srZn9sJYyQb9fGtiOkNgvZpZgZkvNbFVFW35VS5l4M3uzYp8sMbPuzR9p/RrYlqbLYc65kPwHRAPfAKcDccAqYECNMjcDz3odawPbcz4wDFhTx/bLgPcBA0YDS7yOuZHtGAvM8TrOBrYlFRhW8TgR2FjLeyzo90sD2xES+6Xi79y64nEssAQYXaPMXcCLFY8nA296HbcfbWmyHBbKPf+RwGbn3BbnXBHwBuWzjIYk59wC4OBJikwE/urKLQbaVUypEVQa0I6Q4Zzb45z7suJxPrAe6FKjWNDvlwa2IyRU/J0PVyzGVvyreeCy6mzDbwMXWH0Ti3mggW1pMqGc/LsAO6ssZ1L7G/rqip/jb5tZevOE1iQa2t5QcFbFT933zewMr4NpiIqhg6GU986qCqn9cpJ2QIjsFzOLNrOVlM8l9qFzrs594pwrAXKBpOaNsmEa0BZoohwWysm/tm/ymt+a/wd0d84NAj7ieG8gFDWkvaHgS8ovPx8M/AF41+N46mVmrYF/AD9yzuXV3FzLU4Jyv9TTjpDZL865UufcECANGGlmA2sUCZl90oC2NFkOC+XknwlU/RZMA3ZXLeCcO+CcK6xY/BMwvJliawr1tjcUOOfyvv2p65x7D4g1s2SPw6qTmcVSnjBfd869U0uRkNgv9bUj1PYLgHMuB/gUGF9jU+U+MbMYoC1BPhRZV1uaMoeFcvJfBvQ2sx5mFkf5gZ3ZVQvUGHudQPlYZ6iaDXyv4uyS0UCuq7iRTigxs87fjr+a2UjK34MHvI2qdhVxvgSsd849VUexoN8vDWlHqOwXM0sxs3YVj1sAFwJf1yj27WzDANcAn7iKo6fBpCFtacoc5u+Uzp5xzpWY2T3AB5Sf+fOyc26tmT0KZDjnZgM/MLMJQAnl3/w3exZwPcxsBuVnXCSbWSbwCOUHgHDOvQi8R/mZJZuBo8At3kR6cg1oxzXANDMrAY4Bk4Pxg1nhHOAm4KuKcVmAhyifxTaU9ktD2hEq+yUVeNXMoin/gprpnJtT43P/EvCamW2m/HM/2btwT6ohbWmyHKYrfEVEIlAoD/uIiEgjKfmLiEQgJX8RkQik5C8iEoGU/EVEIpCSv4hIBFLyFxGJQEr+IiIR6P8DKqg85TnHMM0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y, \n",
    "\tls=(':'), # 折线图的线条风格\n",
    " \tlw=2,   # 折线图的线宽\n",
    " \tlabel='plot figure')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'-': '_draw_solid',\n",
       " '--': '_draw_dashed',\n",
       " '-.': '_draw_dash_dot',\n",
       " ':': '_draw_dotted',\n",
       " 'None': '_draw_nothing',\n",
       " ' ': '_draw_nothing',\n",
       " '': '_draw_nothing'}"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import matplotlib\n",
    "matplotlib.lines.Line2D.lineStyles"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## scatter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(0.05, 10, 100)\n",
    "y1 = np.random.randn(100) # Return a sample (or samples) from the \"standard normal\" distribution.\n",
    "\n",
    "plt.scatter(x, y1, label='scatter figure')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x, y1, label='scatter figure', marker=\"*\") # 默认为'o'，设置为'*''\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'.': 'point',\n",
       " ',': 'pixel',\n",
       " 'o': 'circle',\n",
       " 'v': 'triangle_down',\n",
       " '^': 'triangle_up',\n",
       " '<': 'triangle_left',\n",
       " '>': 'triangle_right',\n",
       " '1': 'tri_down',\n",
       " '2': 'tri_up',\n",
       " '3': 'tri_left',\n",
       " '4': 'tri_right',\n",
       " '8': 'octagon',\n",
       " 's': 'square',\n",
       " 'p': 'pentagon',\n",
       " '*': 'star',\n",
       " 'h': 'hexagon1',\n",
       " 'H': 'hexagon2',\n",
       " '+': 'plus',\n",
       " 'x': 'x',\n",
       " 'D': 'diamond',\n",
       " 'd': 'thin_diamond',\n",
       " '|': 'vline',\n",
       " '_': 'hline',\n",
       " 'P': 'plus_filled',\n",
       " 'X': 'x_filled',\n",
       " 0: 'tickleft',\n",
       " 1: 'tickright',\n",
       " 2: 'tickup',\n",
       " 3: 'tickdown',\n",
       " 4: 'caretleft',\n",
       " 5: 'caretright',\n",
       " 6: 'caretup',\n",
       " 7: 'caretdown',\n",
       " 8: 'caretleftbase',\n",
       " 9: 'caretrightbase',\n",
       " 10: 'caretupbase',\n",
       " 11: 'caretdownbase',\n",
       " 'None': 'nothing',\n",
       " None: 'nothing',\n",
       " ' ': 'nothing',\n",
       " '': 'nothing'}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import matplotlib\n",
    "matplotlib.markers.MarkerStyle.markers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## xlim() 坐标轴范围"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAD8CAYAAACMwORRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAGTdJREFUeJzt3X9w1fW95/Hnm5OfYDAUUgZJVmAusaASYkOWscVaJRStBadzraZ6t7v9oR0u4grslnaLu7rTGXuvIx1aXdapDK1rA3jptgxwsYxib12USxACV0CLLFsyZAr1SgJiICHv/SOHGGLgnCQn+Z7zOa/HDEO+53zOOW/OyXnx+X6+n+/na+6OiIiEZVjUBYiISOop3EVEAqRwFxEJkMJdRCRACncRkQAp3EVEApQw3M1stZmdMLN/ucz9ZmYrzeywme0zs5tSX6aIiPRFMj33NcDcK9x/BzA5/udB4H8MvCwRERmIhOHu7v8E/OsVmswHfumd3gSKzWxcqgoUEZG+y0nBc4wHjnXbbozf1tSzoZk9SGfvHsst+Gze6FLMjJEFOZR9angKShERCdvu3bv/4u4lidqlItytl9t6XdPA3Z8DngPIHzfZJ3x7JWWjhvPzb1Rx7egRKShFRCRsZvb/kmmXitkyjUBZt+1S4HjCFzaj/YLzaE25gl1EJMVSEe4bgX8XnzUzE2h2908MyfQ0dmQ+hbkxNu9L2FRERPoo4bCMmdUBtwJjzKwR+K9ALoC7rwK2AHcCh4GzwH9I5oXHXJXPPy69labmj/pXuYiIXFbCcHf32gT3O/C3/XnxkqJ8Sory+/NQEUmBtrY2GhsbaW1tjboU6aGgoIDS0lJyc3P79fhUHFAVkQzV2NhIUVEREyZMwKy3uRESBXfn/fffp7GxkYkTJ/brObT8gEgWa21tZfTo0Qr2NGNmjB49ekB7VAp3kTTX0trG7Kd/T0tr26A8v4I9PQ30c1G4i6S57YdOcPjEGbYfOhF1KZJBFO4iaWpR3R6mLN/KkvUNACxZ38CU5VtZVLcn4srSy9GjR/nVr37Vtb137162bNky4OdduXIlU6ZM4f7772fjxo08+eSTA37OoaRwD9Bg78bL0FhcU874UYXkxDp3z3NiRumoQpbMKY+4svSSinBvb2//xG3PPvssW7Zs4cUXX2TevHksW7ZswLUCXLhwISXPk4jCPUDajQ/DhDEjWFxTTvsFZ3heLG3O6E5l5+HDDz/ky1/+MhUVFdxwww2sW7cOgF27dnHzzTdTUVFBdXU1p0+f5ujRo8yaNYubbrqJm266iR07dgCwbNky/vCHPzB9+nR+/OMf89hjj7Fu3TqmT5/OunXr+PDDD/nmN7/JjBkzqKys5Le//S0Aa9as4Z577uErX/kKc+bMuaSu7373uxw5coR58+axYsUK1qxZw8KFCwF47733mDlzJjNmzOCxxx7jqquuAuC1117jrrvu6nqOhQsXsmbNGgAmTJjAE088wec//3leeukl3nvvPebOnctnP/tZZs2axaFDhwb8XvakqZABWVS3h20H/kzbhQ6gczd+2Yb91Ewdy8rayoirk/7YtK+JwtwYi26fzMpX/sjmfU3ceWO0i6527zzMnz5+QM+1detWrrnmGjZv3gxAc3Mz58+f595772XdunXMmDGDlpYWCgsL+fSnP822bdsoKCjgj3/8I7W1tdTX1/Pkk0/y1FNPsWnTJgDGjh1LfX09P/vZzwD4wQ9+wG233cbq1as5deoU1dXVzJ49G4A33niDffv28alPfeqSulatWsXWrVvZvn07Y8aM6QppgEceeYRHHnmE2tpaVq1alfS/taCggNdffx2A22+/nVWrVjF58mR27tzJggULePXVV/v9PvZG4R6QxTXlHGhqofGDs7R3uHbjA/DQLZN4fN71lBTlc3fl+EjP6B6MzsONN97I0qVL+d73vsddd93FrFmz2L9/P+PGjWPGjBkAjBw5Eujs5S9cuJC9e/cSi8V49913k3qN3/3ud2zcuJGnnnoK6Jz++ac//QmAmpqaTwR7Im+88Qa/+c1vAPj617/O0qVLk3rcvffeC8CZM2fYsWMH99xzT9d9586d61MNyVC4B+Tibvyiuj0Mz4txvr0jLXbjpf8qyoq7fo76jO7B6DyUl5eze/dutmzZwve//33mzJnD3Xff3es0wBUrVjB27FgaGhro6OigoKAgqddwdzZs2MB11113ye07d+5kxIjUfTdycnLo6Ojo2u45R/3ia3V0dFBcXMzevXtT9tq90Zh7YC7uxj86u1wLs0lKDcYxgOPHjzN8+HAeeOABli5dyltvvcVnPvMZjh8/zq5duwA4ffo07e3tNDc3M27cOIYNG8YLL7zQdWCyqKiI06dPdz1nz+0vfelL/PSnP6VzpRTYs2dgs41mzpzJhg0bAFi7dm3X7ddeey0HDhzg3LlzNDc388orr/T6+JEjRzJx4kReeukloPM/n4aGhgHV1BuFe2AeumUSry69le/E/37oC5OiLkkCkurOw/79+6murmb69On86Ec/4oc//CF5eXmsW7eOhx9+mIqKCmpqamhtbWXBggX84he/YObMmbz77rtdPeFp06aRk5NDRUUFK1as4Itf/CIHDhzoOqC6fPly2tramDZtGjfccAPLly8fUM0/+clPePrpp6murqapqYmrr74agLKyMr72ta8xbdo07r//fiorLz9U9eKLL/L8889TUVHB9ddf33WQN5Xs4v9mQ62qqsrr6+sjeW0R6XTw4EGmTJmSdPuGY6e4priQkqJ8Tp4+R1PzR0wrLU78wICcPXuWwsJCzIy1a9dSV1c3KOEMvX8+Zrbb3asSPVZj7iKStHQ6BhCV3bt3s3DhQtyd4uJiVq9eHXVJvVK490NLaxtffXYHv15wMyML+rccp4hkplmzZg3KGHmqacy9H3SSkIQkqqFZubKBfi7qufeBThKS0BQUFPD+++9r2d80c3E992Sne/ZG4d4HOklIQlNaWkpjYyMnT56MuhTp4eKVmPpL4d4HOklIQpObm9vvK/1IetOYex/pJCERyQTqufdROq31ISJyOQr3PtI8XxHJBBqWEREJkMJdRCRACncRkQAp3EVEAqRwl2DowuAiH1O4SzC05o/Ix7Seu2S87mv+tHc4OcOM3NgwrfkjQUp2PXf13CXjLa4pZ/yoQnJinQtfac0fEYW7BGAwru0pkukU7hIErfkjciktPyBB0Jo/IpdSuEsQtOaPyKU0LCMiEqCkwt3M5prZO2Z22MyW9XL/vzGz7Wa2x8z2mdmdqS9VRESSlTDczSwGPAPcAUwFas1sao9mPwTWu3slcB/wbKoLFRGR5CXTc68GDrv7EXc/D6wF5vdo48DI+M9XA8dTV6KIiPRVMuE+HjjWbbsxflt3/w14wMwagS3Aw709kZk9aGb1ZlavC/KKiAyeZMLdermt55oFtcAady8F7gReMLNPPLe7P+fuVe5eVVJS0vdqRUQkKcmEeyNQ1m27lE8Ou3wLWA/g7m8ABcCYVBQoIiJ9l0y47wImm9lEM8uj84Dpxh5t/gTcDmBmU+gMd427iIhEJGG4u3s7sBB4GThI56yYt83sCTObF2+2BPiOmTUAdcC/96iWmxQRkeTOUHX3LXQeKO1+22Pdfj4AfC61pYmISH/pDFURkQAp3EVEAqRwFxEJkMJdRCRACncRkQAp3EVEAqRwFxEJkMJdRCRACncRkQAp3EVEAqRwFxEJkMJdRCRACncRkQAp3CV4La1tzH7697S0tkVdisiQUbhL8LYfOsHhE2fYfuhE1KWIDBmFu3QJrYe7qG4PU5ZvZcn6BgCWrG9gyvKtLKrbE3FlIoNP4S5dQuvhLq4pZ/yoQnJindd4z4kZpaMKWTKnPOLKRAafRXU1vKqqKq+vr4/kteVSi+r2sO3An2m70EF7h5MzzMiNDaNm6lhW1lZGXd6AbNnfxKK6PeTlDON8ewcrayu588ZxUZcl0m9mttvdqxK1C6LnHtpwwlALuYe7aV8ThbkxHp1dTmFujM37mqIuSWRIBBHuoQ0nDLUJY0awuKac9gvO8LwY7RecR2vKuXb0iKhLG7CHbpnEq0tv5Tvxvx/6wqSoSxIZEhkd7jpgljqh9nAryoopKcoHoKQon2mlxRFXJDI0cqIuYCAW15RzoKmFxg/Odo4VBzScMNQeumUSj8+7npKifO6uHE9T80dRlyQiA5DRPfeQhxOGmnq4In2T7sf6MjrcIdzhBBFJb+l+rC/jp0I2HDvFNcWFlBTlc/L0OZqaP1KvU0QGTdRTh5OdCpnRY+7QOZxwUUlRftfQgojIYMiUY30ZPywjIjKUMuVYn8JdBizdDyyJpFomHOvL+GEZiV73A0vzp4+PuhyRQZcJU4cz/oCqRCfqA0si2Sir1paRaIS8Jo1IplO4S79lyoElkWykcJcByYQDSyLZSAdUZUAy4cCSpEZLaxtffXYHv15wMyMLcqMuRxJIquduZnPN7B0zO2xmyy7T5mtmdsDM3jazX6W2TElXWpMme6T76fZyqYSzZcwsBrwL1ACNwC6g1t0PdGszGVgP3ObuH5jZp939ir8BQzVbRr0NkYHRrKj0ksrZMtXAYXc/4u7ngbXA/B5tvgM84+4fACQK9qGk3obIwGhWVGZKJtzHA8e6bTfGb+uuHCg3s/9jZm+a2dzensjMHjSzejOrP3nyZP8qTpIu5CGSGpoVlZmSCXfr5baeYzk5wGTgVqAW+LmZfWLw1d2fc/cqd68qKSnpa619ot6GSOpoVlTmSWa2TCNQ1m27FDjeS5s33b0N+L9m9g6dYb8rJVX2w8XexqK6PQzPi3G+vUO9DZF+0qyozJNMz30XMNnMJppZHnAfsLFHm98AXwQwszF0DtMcSWWh/aHehkhqaFZU5knYc3f3djNbCLwMxIDV7v62mT0B1Lv7xvh9c8zsAHAB+E/u/v5gFp4M9TZEJFtp4TARkQyihcNERLKYwl1EJEAKdxGRACncRUQCpHAXEQmQwl0GjS6cLRIdhbsMGi3aJhIdzXOXlNMSsSKDR/PcJTJatE0kegp3STktESsSPYW7DAot2iYSLV0gWwZFpizapsswSqjUc5dBkSlLxGpGj4RKs2UkK2lGj2QqzZYRuQLN6JHQKdwlK2lGj4RO4S5ZSzN6JGSaLSNZK1Nm9Ij0h8JdslZF2cczeEqK8rtm94iEQMMyIiIBUriLiARI4S4iEiCFu4hIgBTuIiIBUriLiARI4S4iEiCFu4hIgBTuIiIBUriLiARI4S4iEiCFu4hIgBTuIiIBUriLiARI4S4iEiCFu4hIgJIKdzOba2bvmNlhM1t2hXZ/bWZuZgmvzC0iIoMnYbibWQx4BrgDmArUmtnUXtoVAYuAnakuUkRE+iaZnns1cNjdj7j7eWAtML+Xdv8d+DugNYX1iYhIPyQT7uOBY922G+O3dTGzSqDM3Tdd6YnM7EEzqzez+pMnT/a5WBERSU4y4W693OZdd5oNA1YASxI9kbs/5+5V7l5VUlKSfJUiItInyYR7I1DWbbsUON5tuwi4AXjNzI4CM4GNOqgqIhKdZMJ9FzDZzCaaWR5wH7Dx4p3u3uzuY9x9grtPAN4E5rl7/aBULJKhWlrbmP3072lpbYu6FMkCCcPd3duBhcDLwEFgvbu/bWZPmNm8wS5QJBTbD53g8IkzbD90IupSJAuYuyduNQiqqqq8vl6dewnforo9bDvwZ9oudNDe4eQMM3Jjw6iZOpaVtZVRlycZxsx2u3vCYW+doSoyyBbXlDN+VCE5sc65CTkxo3RUIUvmlEdcmYRM4S4yyCaMGcHimnLaLzjD82K0X3AerSnn2tEjoi5NAqZwFxkCm/Y1UZgb49HZ5RTmxti8rynqkiRwOVEXIJINHrplEo/Pu56SonzurhxPU/NHUZckgVO4iwyBirLirp9LivIpKcqPsBrJBhqWEREJkMJdRCRACncRkQAp3EVELiOTl4xQuIuIXEYmLxmh5QdERHpI5yUjtPyAiEg/hbBkhMJdRKSHEJaMULiLiPQi05eM0BmqIiK9yPQlIxTuIiK9yPQlIzQsIyISIIW7iEiAFO4iIgFSuEtSMvk0bJFspHCXpGTyadgi2UjLD8gVpfNp2CLZSMsPSEqEcBq2SDZSuMsVhXAatkg2UrhLQpl+GrZINtIZqpJQpp+GLZKNFO6SUKafhi2SjTQsIyISIIW7iEiAFO4iIgFSuIuIBEjhLiISIIW7iEiAFO4iIgFKKtzNbK6ZvWNmh81sWS/3LzazA2a2z8xeMbNrU1+qiIgkK2G4m1kMeAa4A5gK1JrZ1B7N9gBV7j4N+Afg71JdqIiIJC+Znns1cNjdj7j7eWAtML97A3ff7u5n45tvAqWpLXNw6AIUmUefmUhykgn38cCxbtuN8dsu51vAP/Z2h5k9aGb1ZlZ/8uTJ5KscJLoARebRZyaSnIQX6zCze4Avufu349t/A1S7+8O9tH0AWAh8wd3PXel5o7xYhy5AkXn0mYl0SuXFOhqBsm7bpcDxXl5wNvBfgHmJgj1qugBF5tFnJtI3yYT7LmCymU00szzgPmBj9wZmVgn8TzqDPe33l3UBisyjz0ykbxKGu7u30znU8jJwEFjv7m+b2RNmNi/e7O+Bq4CXzGyvmW28zNOlDV2AIvPoMxNJXtZeILvh2CmuKS6kpCifk6fP0dT8EdNKixM/UCKjz0wk+TH3rL1Yhy5AkXn0mYkkT8sPiIgESOEuIhIghbuISIAU7iIiAVK4i4gESOEuIhIghbuISIAU7iIiAVK4i4gESOEuIhIghbuISIAU7iIiAVK4i4gESOEuIhIghbuISIAU7iIiAVK4i4gESOEuIhIghbuISIAU7lmmpbWN2U//npbWtqhLEQlWOnzPFO5ZZvuhExw+cYbth05EXYpIsNLhe2buHskLV1VVeX19fSSvnY0W1e1h24E/03ahg/YOJ2eYkRsbRs3UsaysrYy6PJEgDMX3zMx2u3tVonbquWeJxTXljB9VSE7MAMiJGaWjClkypzziytJXOuxaS2ZJ5ns2VL9XCvcsMWHMCBbXlNN+wRmeF6P9gvNoTTnXjh4RdWlpKx12rSWzJPM9G6rfK4V7Ftm0r4nC3BiPzi6nMDfG5n1NUZeUlhbV7WHK8q0sWd8AwJL1DUxZvpVFdXsirkwyweW+Z0P9e6Ux9yzScOwU1xQXUlKUz8nT52hq/ohppcVRl5V2jv7lQ779y3oaPzhLa1sHBbnDKBs1nJ9/oyqpPZ2W1ja++uwOfr3gZkYW5A5BxZJOLvc9G+jv1UUac5dPqCgrpqQoH4CSonwF+2UMdAhLwznZ7XLfs6EeGlW4i/SiP0NYGs6RRIZyaFTDMiK96M8QVqp2uyVcqRga1bCMyAD0ZwhLM5IkkaEcGlW4i6SQZiRJusiJugCRkDx0yyQen3c9JUX53F05nqbmj6IuSbKUeu4iKdTf3W6dDSuppnAXSQOaPimpllS4m9lcM3vHzA6b2bJe7s83s3Xx+3ea2YRUFyoSoiimT2ovITskDHcziwHPAHcAU4FaM5vao9m3gA/c/a+AFcCPU12oSIiiWNBNewnZIZmeezVw2N2PuPt5YC0wv0eb+cAv4j//A3C7mVnqyhQJ01BOn9RJVtklmdky44Fj3bYbgX97uTbu3m5mzcBo4C/dG5nZg8CD8c0zZvZOf4oOxBh6vD9ZLmvfj5xR10yy3IKRHWdPNQ0bXjxu/qqPWto/aGohxe+H5eTl5xSP+yuL5eRhNgz3Dr/Qfv6dU02Hf/r18+dS+VoplrW/G5dxXTKNkgn33nrgPU9rTaYN7v4c8FwSrxk8M6tP5iyzbKH341J6Pz6m9+JSZpbUqf3JDMs0AmXdtkuB45drY2Y5wNXAvyZTgIiIpF4y4b4LmGxmE80sD7gP2NijzUbgG/Gf/xp41aNatEZERBIPy8TH0BcCLwMxYLW7v21mTwD17r4ReB54wcwO09ljv28wiw6EhqcupffjUno/Pqb34lJJvR+RrQopIiKDR2eoiogESOEuIhIghfsQM7PVZnbCzP4l6lrSgZmVmdl2MztoZm+b2SNR1xQVMysws382s4b4e/F41DWlAzOLmdkeM9sUdS1RMrOjZrbfzPYmMx1SY+5DzMxuAc4Av3T3G6KuJ2pmNg4Y5+5vmVkRsBu4290PRFzakIuf1T3C3c+YWS7wOvCIu78ZcWmRMrPFQBUw0t3virqeqJjZUaDK3ZM6oUs99yHm7v+EzgHo4u5N7v5W/OfTwEE6z3jOOt7pTHwzN/4nq3tfZlYKfBn4edS1ZBqFu6SN+GqilcDOaCuJTnwIYi9wAtjm7ln7XsT9BPjPQEfUhaQBB35nZrvjS7lckcJd0oKZXQVsAP6ju7dEXU9U3P2Cu0+n80zwajPL2qE7M7sLOOHuu6OuJU18zt1vonOF3r+ND/FelsJdIhcfX94AvOjuv466nnTg7qeA14C5EZcSpc8B8+JjzWuB28zsf0VbUnTc/Xj87xPA/6Zzxd7LUrhLpOIHEZ8HDrr701HXEyUzKzGz4vjPhcBs4FC0VUXH3b/v7qXuPoHOs95fdfcHIi4rEmY2Ij7hADMbAcwBrjjjTuE+xMysDngDuM7MGs3sW1HXFLHPAX9DZ69sb/zPnVEXFZFxwHYz20fnmk7b3D2rp/9Jl7HA62bWAPwzsNndt17pAZoKKSISIPXcRUQCpHAXEQmQwl1EJEAKdxGRACncRUQCpHAXEQmQwl1EJED/H5VlnatLeuoaAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(0.05, 10, 100)\n",
    "y1 = np.random.randn(100) # Return a sample (or samples) from the \"standard normal\" distribution.\n",
    "\n",
    "plt.scatter(x, y1, label='scatter figure', marker=\"*\") # 默认为'o'，设置为'*''\n",
    "plt.legend()\n",
    "\n",
    "plt.xlim(0.05, 5)\n",
    "plt.ylim(0,1)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## xlabel 坐标轴标签"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAEKCAYAAAD9xUlFAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAGtlJREFUeJzt3X2QVfWd5/H3h+4GWmxsAx0WaVZwl46g0mAahkoGJ1Ga4EPQmhqjRHeSSTaacgguD5mQTHCjM9mYxJIUiVniRotMojwYZg0lLMZVNHF9GBp5cGxR0WFih55AHOVBRbvp7/5xL8emaeACffrcpj+vqi7uOed37/1yqOLT53d+v99RRGBmZgbQJ+sCzMyseDgUzMws4VAwM7OEQ8HMzBIOBTMzSzgUzMwskVooSLpX0k5J/3yE45K0SNI2SVskXZhWLWZmVpg0rxSWANOOcvxSYFT+5wbgf6ZYi5mZFSC1UIiI3wD/fpQmVwL/EDnPAJWShqZVj5mZHVtpht89DHi93XZTfl9zx4aSbiB3NcGAAQM+eu6553ZLgWZmp4oNGzb8MSKqjtUuy1BQJ/s6XXMjIu4G7gaoq6uLhoaGNOsyMzvlSPrXQtplOfqoCRjebrsa2JFRLWZmRrahsAr4y/wopEnA7og4rOvIzMy6T2rdR5KWAp8ABktqAv47UAYQEYuBNcBlwDbgHeCv0qrFzMwKk1ooRMSMYxwP4K/T+n4zS09LSwtNTU3s378/61Ksg/79+1NdXU1ZWdkJvT/LG81m1kM1NTVRUVHBiBEjkDobM2JZiAjeeOMNmpqaGDly5Al9hpe5MLPjtn//fgYNGuRAKDKSGDRo0EldwTkUzOyEOBCK08n+uzgUzMws4VAwKxJ79rcw5c4n2LO/JetSeoXt27dz//33J9ubNm1izZo1J/25ixYtYvTo0Vx33XWsWrWK22+//aQ/szs5FMyKxLqtO9m2cx/rtu7MupReoStCobW19bB9P/7xj1mzZg333Xcf06dPZ/78+SddK8CBAwe65HOOxaFglrFZSzcyesFa5q7YDMDcFZsZvWAts5ZuzLiyrtWVV0Jvv/02l19+ObW1tZx//vksX74cgPXr1/Oxj32M2tpaJk6cyN69e9m+fTuTJ0/mwgsv5MILL+Spp54CYP78+fz2t79l3LhxfPe73+WWW25h+fLljBs3juXLl/P222/zhS98gQkTJjB+/Hh+9atfAbBkyRKuvvpqPv3pTzN16tRD6vryl7/Ma6+9xvTp01m4cCFLlixh5syZALz66qtMmjSJCRMmcMstt3D66acD8Pjjj3PFFVcknzFz5kyWLFkCwIgRI7jtttv40z/9Ux544AFeffVVpk2bxkc/+lEmT57M1q1bT/pcduQhqWYZm1NfQ2PzHprefIfWtqC0RFSfWc7cqTVZl9al2l8JXTlu2El91tq1aznrrLNYvXo1ALt37+b999/nmmuuYfny5UyYMIE9e/ZQXl7Ohz/8YR555BH69+/PK6+8wowZM2hoaOD222/njjvu4KGHHgJgyJAhNDQ08KMf/QiAb3zjG1x88cXce++9vPXWW0ycOJEpU6YA8PTTT7NlyxY+9KEPHVLX4sWLWbt2LevWrWPw4MHJf+4AN998MzfffDMzZsxg8eLFBf9d+/fvz5NPPgnAJZdcwuLFixk1ahTPPvssN910E4899tgJn8fOOBTMMjZi8ADm1Ncwa+lGTutbwvutbcyur+HsQQOyLq1LzFq6kUca/0DLgTYgdyU0f+Xz1I8ZwqIZ40/oMy+44ALmzZvH1772Na644gomT57M888/z9ChQ5kwYQIAAwcOBHJXFTNnzmTTpk2UlJTw8ssvF/Qdv/71r1m1ahV33HEHkBuG+7vf/Q6A+vr6wwLhWJ5++mkefPBBAD772c8yb968gt53zTXXALBv3z6eeuoprr766uTYe++9d1w1FMKhYFYEHtrSTHlZCbMuGcWiR19h9ZZmLrvg1Hi8SBpXQjU1NWzYsIE1a9bw9a9/nalTp3LVVVd1Ohxz4cKFDBkyhM2bN9PW1kb//v0L+o6IYOXKlXzkIx85ZP+zzz7LgAFdF9ilpaW0tbUl2x3nGBz8rra2NiorK9m0aVOXfXdnfE/BrAjceNE5PDbvE3wp/+eNf3ZO1iV1mYNXQq0HgtP6ltB6IE76SmjHjh2cdtppXH/99cybN4/nnnuOc889lx07drB+/XoA9u7dS2trK7t372bo0KH06dOHn//858kN24qKCvbu3Zt8ZsftT33qU/zwhz8ktyIPbNx4cvd4Jk2axMqVKwFYtmxZsv/ss8+msbGR9957j927d/Poo492+v6BAwcycuRIHnjgASAXWps3bz6pmjrjUDArArXDK6mq6AdAVUU/xlZXZlxR1zp4JTR7Sg3lZSWs3nJyCyI///zzTJw4kXHjxvHtb3+bb37zm/Tt25fly5fzla98hdraWurr69m/fz833XQTP/vZz5g0aRIvv/xy8pv32LFjKS0tpba2loULF/LJT36SxsbG5EbzggULaGlpYezYsZx//vksWLDgpGr+wQ9+wJ133snEiRNpbm7mjDPOAGD48OF85jOfYezYsVx33XWMH3/kLrX77ruPe+65h9raWs4777zk5ndX0sEU7Cn8kB2z7L344ouMHj264PabX3+LsyrLqarox66979G8+91TLviO5Z133qG8vBxJLFu2jKVLl6bynzp0/u8jaUNE1B3rvb6nYGapqx3+QQBUVfRLrop6kw0bNjBz5kwigsrKSu69996sS+qUQ8HMrBtMnjw5lXsAXc33FMzshPS0rufe4mT/XRwKZnbc+vfvzxtvvOFgKDIHn6dQ6LDbzrj7yMyOW3V1NU1NTezatSvrUqyDg09eO1EOBbMj2LO/hT//8VP8400fY2D/E3u04amqrKzshJ/sZcXN3UdmR+BVS6038jwFsw7ar9XT2haU9hFlJX1Oaq0es6wVOk/BVwpmHcypr2HYmeWUluTW0TlVVy0164xDwayDNNbqMespHApmnejqtXrMegqPPjLrxI0XncOt08+jqqIfV40fRvPud7MuyaxbOBTMOuG1eqy3cveRmZklHApmZpZwKJiZFYk9+1uYcucT7NnfklkNDgUzsyJRDLPoPaPZzCxj3TGL3jOazcx6iGKaRe9QMDPLWDHNoncomJkVgWKZRe/Ja2ZmRaBYZtGneqUgaZqklyRtkzS/k+P/UdI6SRslbZF0WZr1mFlOMQx9tEPVDq9MZs5XVfRjbHXlMd6RjtRCQVIJcBdwKTAGmCFpTIdm3wRWRMR44Frgx2nVY2YfKIahj1ac0uw+mghsi4jXACQtA64EGtu1CWBg/vUZwI4U6zHr9doPfQSYu2Iz81c+7wcIWSLN7qNhwOvttpvy+9r7FnC9pCZgDfCVzj5I0g2SGiQ1+EHhZieumIY+WnFKMxTUyb6OM+VmAEsiohq4DPi5pMNqioi7I6IuIuqqqqpSKNWsdyimoY9WnNIMhSZgeLvtag7vHvoisAIgIp4G+gODU6zJrNcrlqGPVpzSvKewHhglaSTwe3I3kj/boc3vgEuAJZJGkwsF9w+ZpahYhj5acUotFCKiVdJM4GGgBLg3Il6QdBvQEBGrgLnA/5I0m1zX0uejpy3GZNbD+AFCdjSpTl6LiDXkbiC333dLu9eNwMfTrMHMzArnZS7MzCzhUDAzs4RDwczMEg4FMzNLOBTMzCzhUDAzs4RDwczMEg4FMzNLOBTMzCzhUDAzs4RDwczMEg4FMzNLOBTMzCzhUDAzs4RDwczMEg4FMzNLOBTMzCzhUDAzs4RDwczMEg4FMzNLOBTMzCzhUDAzs4RDwczMEg4FMzNLOBTMzCzhUDAzs0SvDoU9+1uYcucT7NnfknUpZmZFoVeHwrqtO9m2cx/rtu7MuhQzs6KgiMi6huNSV1cXDQ0NJ/UZs5Zu5JHGP9ByoI3WtqC0jygr6UP9mCEsmjG+iyo1MysekjZERN2x2vXKK4U59TUMO7Oc0hIBUFoiqs8sZ+7UmowrMzPLVq8MhRGDBzCnvobWA8FpfUtoPRDMrq/h7EEDsi7NzCxTvTIUAB7a0kx5WQmzp9RQXlbC6i3NWZdkZpa50qwLyMqNF53DrdPPo6qiH1eNH0bz7nezLsnMLHO9NhRqh1cmr6sq+lFV0S/DaszMikOq3UeSpkl6SdI2SfOP0OYzkholvSDp/jTrMTOzo0vtSkFSCXAXUA80AeslrYqIxnZtRgFfBz4eEW9K+nBa9ZiZ2bGleaUwEdgWEa9FxPvAMuDKDm2+BNwVEW8CRIRnkZmZZSjNUBgGvN5uuym/r70aoEbS/5P0jKRpnX2QpBskNUhq2LVrV0rlmplZmqGgTvZ1nD5dCowCPgHMAH4qqfKwN0XcHRF1EVFXVVXV5YWamVlOmqHQBAxvt10N7Oikza8ioiUi/gV4iVxImJlZBtIMhfXAKEkjJfUFrgVWdWjzIPBJAEmDyXUnvZZiTWbWw3l143SlFgoR0QrMBB4GXgRWRMQLkm6TND3f7GHgDUmNwDrgqxHxRlo1mVnP59WN09UrV0k1s57HqxufHK+SalYgd0f0DF7duHs4FKzXc3dEz+DVjbuHQ8F6rVlLNzJ6wVrmrtgMwNwVmxm9YC2zlm7MuDI7Eq9unL5euyCe2Zz6Ghqb99D05ju5Pmp3RxQ9r26cvuO6UpDUR9LAtIox607ujuh5aodXJisaV1X0Y2z1YXNd7SQdMxQk3S9poKQBQCPwkqSvpl+aWfrcHWF2qEK6j8ZExB5J1wFrgK8BG4Dvp1qZWTdwd4TZoQrpPiqTVAZcRX5JCg5fw8isW3T18NGe3h3h4bTW1QoJhZ8A24EBwG8knQ3sSbMosyPx8NFD+XxYVzuhGc2SSvPLWHQ7z2junTyb9VA+H3a8Cp3RfMR7CpKuj4hfSJpzhCZ3nnB1ZsfJw0cP5fNhaTla99HBcXkVR/gx6zYePnoonw9LyxFDISJ+kv/z1o4/wHe6rUKzPA8fPZTPh6XhmPcUJD0OfD4itue3JwA/jYja1KvrhO8p9F6bX3+LsyrLqarox66979G8+90eN1qoK/l82PE46XsK7XwHWCtpEblnLF8K/NVJ1md23GqHf/AfXlVFv2QoaW/l82FpOGYoRMTDkr4MPAL8ERgfEf+WemVmZtbtClnmYgHwQ+Ai4FvA45IuT7kuMzPLQCHdR4OBiRHxLvC0pLXAT4HVqVZmZmbdrpDuo5s7bP8rUJ9aRWZmlpljhoKkKnKL4I0B+h/cHxEXp1iXmZlloJC1j+4DXgRGAreSWwdpfYo1mZlZRgoJhUERcQ/QEhFPRMQXgEkp12VmZhko5EbzwTV5m/OjjnYA1emVZGZmWSkkFP5e0hnAXHJDUwcCs1OtyszMMlHI6KOH8i93A59MtxwzM8tSIfcUEpKeS6sQMzPL3nGFAqBUqjAzs6JQyDIXMyUdXHnLs5jNzE5hhVwp/AegQdIK4ElJvlowMztFHTMUIuKbwCjgHuDzwCuS/oek/5RybWZm1s0KuqcQuSfx/Fv+pxU4E/ilpO+lWJuZmXWzQtY+mgV8jtyzFH4KfDUiWiT1AV4B/ibdEs3MrLsUunT2n+dXR01ERJukK9Ipy8zMslDI5LVbjnLsxa4tx8zMsnS88xTMzOwUlmooSJom6SVJ2yTNP0q7v5AUkurSrMfMzI4utVCQVALcBVxK7gE9MySN6aRdBTALeDatWszMrDBpXilMBLZFxGsR8T6wDLiyk3Z/B3wP2J9iLWZmVoA0Q2EY8Hq77ab8voSk8cDwdiuxdkrSDZIaJDXs2rWr6ys1MzMg3VDobDmMSA7m5jksJPechqOKiLsjoi4i6qqqqrqwRDMzay/NUGgChrfbrib31LaDKoDzgcclbSf3iM9VvtlsZpadNENhPTBK0khJfYFrgVUHD0bE7ogYHBEjImIE8AwwPSIaUqzJzMyOIrVQiIhWYCbwMPAisCIiXpB0m6TpaX2vmZmduEKWuThhEbEGWNNhX6czpCPiE2nWYmZmx+YZzWZmlnAomJlZwqFgZmYJh4KZmSUcCmZmlnAomJlZwqFgZmYJh4KZmSUcCmZmlnAomJlZwqFgZmYJh4KZmSUcCmZmlnAomJlZwqFgZmYJh4KZmSUcCmZmlnAomJlZwqFgZmYJh4KZmSUcCmZmlnAomJlZwqFgZmYJh4KZmSUcCmZmlnAomJlZwqFgZmYJh4JZF9uzv4Updz7Bnv0tWZdidtwcCmZdbN3WnWzbuY91W3dmXYrZcVNEZF3Dcamrq4uGhoasyzA7zKylG3mk8Q+0HGijtS0o7SPKSvpQP2YIi2aMz7o86+UkbYiIumO185WCWReZU1/DsDPLKS0RAKUlovrMcuZOrUnauGvJip1DwayLjBg8gDn1NbQeCE7rW0LrgWB2fQ1nDxqQtHHXkhU7h4JZF3poSzPlZSXMnlJDeVkJq7c0A7mupdEL1jJ3xWYA5q7YzOgFa5m1dGOW5ZodpjTrAsxOJTdedA63Tj+Pqop+XDV+GM273wVyXUuNzXtoevOd3P2GTrqWzIpBqlcKkqZJeknSNknzOzk+R1KjpC2SHpV0dpr1mKWtdnglVRX9AKiq6MfY6kqgsK4ls2KQWihIKgHuAi4FxgAzJI3p0GwjUBcRY4FfAt9Lqx6zrB2pa8msmKTZfTQR2BYRrwFIWgZcCTQebBAR69q1fwa4PsV6zDJ1pK4ls2KSZvfRMOD1dttN+X1H8kXg/3R2QNINkhokNezatasLSzTrPkfqWjrVeRhuz5JmKKiTfZ3OlJN0PVAHfL+z4xFxd0TURURdVVVVF5ZoZmnzMNyeJc3uoyZgeLvtamBHx0aSpgB/C/xZRLyXYj1m1o3az/CG3DDc+Suf9wzvIpfmlcJ6YJSkkZL6AtcCq9o3kDQe+AkwPSL8a4TZKaSQGd5WfFILhYhoBWYCDwMvAisi4gVJt0manm/2feB04AFJmyStOsLHmVkP42G4PVOqk9ciYg2wpsO+W9q9npLm95tZtg4Ow511ySgWPfoKq7c0c9kFQ7Muy47CM5rNLDUehtvzOBTMLDW1wz8YdltV0S8ZkmvFywvimZlZwqFgZmYJh4KZmSUcCmZmlnAomJlZwqFgZmYJh4KZmSUcCmZmlnAomJlZwqFgZmYJh4KZmSUcCmZmlnAomJlZwqFgZmYJh4KZmSUcCidgz/4Wptz5BHv2t2RdiplZl3IonIB1W3eybec+1m3dmXUpZmZdShGRdQ3Hpa6uLhoaGjL57llLN/JI4x9oOdBGa1tQ2keUlfShfswQFs0Yn0lNZmaFkLQhIuqO1c5XCsdhTn0Nw84sp7REAJSWiOozy5k7tSbjyszMuoZD4TiMGDyAOfU1tB4ITutbQuuBYHZ9DWcPGpB1aWZmXcKhcJwe2tJMeVkJs6fUUF5WwuotzVmXZGbWZUqzLqCnufGic7h1+nlUVfTjqvHDaN79btYlmZl1GYfCcaodXpm8rqroR1VFvwyrMTPrWu4+MjOzhEPBzMwSDgUzM0s4FMzMLOFQMDOzhEPBzMwSDgUzM0s4FMzMLOFQMDOzhEPBzMwSqYaCpGmSXpK0TdL8To73k7Q8f/xZSSPSrMfMzI4utVCQVALcBVwKjAFmSBrTodkXgTcj4j8DC4HvplWPmZkdW5pXChOBbRHxWkS8DywDruzQ5krgZ/nXvwQukaQUazIzs6NIc5XUYcDr7babgD85UpuIaJW0GxgE/LF9I0k3ADfkN/dJeimVinuGwXQ4P72cz8ehfD4+UJznQn1KygYNP7fljde3Em0HuvGbP1JIozRDobPf+Ds+ELqQNkTE3cDdXVFUTyepoZDnrPYWPh+H8vn4gM/FoSQV9HD7NLuPmoDh7bargR1HaiOpFDgD+PcUazIzs6NIMxTWA6MkjZTUF7gWWNWhzSrgc/nXfwE8FhGHXSmYmVn3SK37KH+PYCbwMFAC3BsRL0i6DWiIiFXAPcDPJW0jd4VwbVr1nELcjXYon49D+Xx8wOfiUAWdD/kXczMzO8gzms3MLOFQMDOzhEOhh5B0r6Sdkv4561qKgaThktZJelHSC5JuzrqmrEjqL+mfJG3On4tbs66pGEgqkbRR0kNZ15IlSdslPS9pUyHDUn1PoYeQdBGwD/iHiDg/63qyJmkoMDQinpNUAWwAroqIxoxL63b5VQAGRMQ+SWXAk8DNEfFMxqVlStIcoA4YGBFXZF1PViRtB+oioqCJfL5S6CEi4jd4DkciIpoj4rn8673Ai+RmyPc6kbMvv1mW/+nVv+1JqgYuB36adS09jUPBerz86rrjgWezrSQ7+a6STcBO4JGI6LXnIu8HwN8AbVkXUgQC+LWkDfklg47KoWA9mqTTgZXAf4uIPVnXk5WIOBAR48itHDBRUq/tYpR0BbAzIjZkXUuR+HhEXEhuxeq/zndFH5FDwXqsfP/5SuC+iPjHrOspBhHxFvA4MC3jUrL0cWB6vi99GXCxpF9kW1J2ImJH/s+dwP8mt4L1ETkUrEfK31y9B3gxIu7Mup4sSaqSVJl/XQ5MAbZmW1V2IuLrEVEdESPIrZLwWERcn3FZmZA0ID8QA0kDgKnAUUcwOhR6CElLgaeBj0hqkvTFrGvK2MeB/0Lut8BN+Z/Lsi4qI0OBdZK2kFtz7JGI6NXDMC0xBHhS0mbgn4DVEbH2aG/wkFQzM0v4SsHMzBIOBTMzSzgUzMws4VAwM7OEQ8HMzBIOBbNuIOnLkv4y6zrMjsVDUs3MLOErBbMOJE2QtCX/nIIB+WcUnN+hzaclPZtfr///ShqS379I0i3515+S9BtJfSR9S9K8/P5Zkhrz37Gs+/+GZkfmKwWzTkj6e6A/UA40RcR3Ohw/E3grIkLSfwVGR8RcSaeRm1U8E1gMXBYRr0r6FrAvIu6QtAMYGRHvSarMr1dkVhRKsy7ArEjdRu4/9/3ArE6OVwPL8w/76Qv8C0BEvCPpS8BvgNkR8Won790C3CfpQeDBNIo3O1HuPjLr3IeA04EKoL+kbx9cYyl//IfAjyLiAuBGclcVB10AvAGcdYTPvhy4C/gosEGSfzmzouFQMOvc3cAC4D7guxHxtxExLv/MAoAzgN/nX3/u4JsknQ3MJffQn0sl/Un7D5XUBxgeEevIPQSmklz4mBUF/4Zi1kF+6GhrRNwvqQR4StLFEfFYu2bfAh6Q9HvgGWBku+W850XEjvxKtkskTWj3vhLgF5LOAAQs9D0FKya+0WxmZgl3H5mZWcKhYGZmCYeCmZklHApmZpZwKJiZWcKhYGZmCYeCmZkl/j9sNBMQHunqZAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(0.05, 10, 100)\n",
    "y1 = np.random.randn(100) # Return a sample (or samples) from the \"standard normal\" distribution.\n",
    "\n",
    "plt.scatter(x, y1, label='scatter figure', marker=\"*\") # 默认为'o'，设置为'*''\n",
    "plt.legend()\n",
    "\n",
    "plt.xlim(0.05, 5)\n",
    "plt.ylim(0,1)\n",
    "\n",
    "plt.xlabel(\"x-axis\")\n",
    "plt.ylabel('y-axis')\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 设置xlabel参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fontdict = {\n",
    "    'fontsize'            : 'xx-large',\n",
    "    'verticalalignment'   : 'baseline',\n",
    "    'horizontalalignment' : 'center'\n",
    "    }\n",
    "# Valid font size are xx-small, x-small, small, medium, large, x-large, xx-large, larger, smaller, None\n",
    "# Vertical alignment must be one of ('top', 'bottom', 'center', 'baseline')\n",
    "# Horizontal alignment must be one of ('center', 'right', 'left')\n",
    "x = np.linspace(0.05, 10, 100)\n",
    "y1 = np.random.randn(100) # Return a sample (or samples) from the \"standard normal\" distribution.\n",
    "\n",
    "plt.scatter(x, y1, label='scatter figure', marker=\"*\") # 默认为'o'，设置为'*''\n",
    "plt.legend()\n",
    "\n",
    "plt.xlim(0.05, 5)\n",
    "plt.ylim(0,1)\n",
    "\n",
    "plt.xlabel(\"x-axis\", fontdict=fontdict)\n",
    "plt.ylabel('y-axis')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## grid 刻度线\n",
    "\n",
    "Signature: plt.grid(b=None, which='major', axis='both', **kwargs) \n",
    "\n",
    "kwargs:\n",
    "color='r', linestyle='-', linewidth=2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x, y1, label='scatter figure', marker=\"*\") # 默认为'o'，设置为'*''\n",
    "plt.legend()\n",
    "kwargs = {\n",
    "    'color':'r', \n",
    "    'linestyle':':', \n",
    "    'linewidth':1\n",
    "}\n",
    "plt.grid(**kwargs)\n",
    "# 或者直接调用：\n",
    "# plt.grid(color='r', linestyle=':')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## axhline 水平参考线\n",
    "\n",
    "Signature: plt.axhline(y=0, xmin=0, xmax=1, hold=None, **kwargs)\n",
    "\n",
    "- y 水平参考线的出发点\n",
    "- c 参考线的线条颜色\n",
    "- ls 参考线的线条风格\n",
    "- lw 参考线的线条宽度\n",
    "\n",
    "## axvline 竖直参考线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y, \n",
    "\tls=(':'), # 折线图的线条风格\n",
    " \tlw=2,   # 折线图的线宽\n",
    " \tlabel='plot figure')\n",
    "plt.legend()\n",
    "\n",
    "plt.axhline(y=0.5,\n",
    "           xmin=0,\n",
    "           xmax=1,\n",
    "           c='r',\n",
    "           ls='--',\n",
    "           lw=2)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y, \n",
    "\tls=(':'), # 折线图的线条风格\n",
    " \tlw=2,   # 折线图的线宽\n",
    " \tlabel='plot figure')\n",
    "plt.legend()\n",
    "\n",
    "plt.axhline(y=0.5,\n",
    "           xmin=0.2,  # 控制起始比例\n",
    "           xmax=0.4,\n",
    "           c='r',\n",
    "           ls='--',\n",
    "           lw=2)\n",
    "'''\n",
    "xmin : scalar, optional, default: 0\n",
    "    Should be between 0 and 1, 0 being the far left of the plot, 1 the far right of the plot.\n",
    "xmax : scalar, optional, default: 1\n",
    "    Should be between 0 and 1, 0 being the far left of the plot, 1 the far right of the plot.\n",
    "'''\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y, \n",
    "\tls=(':'), # 折线图的线条风格\n",
    " \tlw=2,   # 折线图的线宽\n",
    " \tlabel='plot figure')\n",
    "plt.legend()\n",
    "\n",
    "plt.axhline(y=0.5,\n",
    "           xmin=0,\n",
    "           xmax=0.5,\n",
    "           c='r',\n",
    "           ls='--',\n",
    "           lw=2)\n",
    "plt.axvline(4, ymin=0.6,ymax=0.8,color='g',linestyle=\":\",linewidth=2)\n",
    "           \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## axvspan 竖直参考区域\n",
    "Signature: plt.axvspan(xmin, xmax, ymin=0, ymax=1, hold=None, **kwargs)\n",
    "\n",
    "## axhspan 水平参考区域"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## axvspan 竖直参考区域\n",
    "plt.plot(x, y, \n",
    "\tls='-.', # 折线图的线条风格\n",
    " \tlw=2,   # 折线图的线宽\n",
    " \tlabel='plot figure')\n",
    "\n",
    "plt.legend()\n",
    "plt.axvspan(xmin=4, # 起始位置\n",
    "\t\t\txmax=6,\t# 终止位置\n",
    "\t\t\tymin=0.4, # 起始比例*****和上面不一样\n",
    "\t\t\tymax=1,\n",
    "\t\t\tfacecolor='y', # 填充颜色\n",
    "\t\t\talpha=0.3) # 填充透明度\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX8AAAD8CAYAAACfF6SlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAIABJREFUeJzt3Xd8VFX6x/HPk0kjIaEkAWJClQ5SR1BhFRQVRUEsgL0uqy42dBXXXdeyy1pwLQuui2Jb/YHYdhFRWRVREJCEJt1ICZGWhFBCeub5/ZGYDTEQyExyJzPP+/XixcydM3OeSfnOzbn3niOqijHGmOAS4nQBxhhj6p+FvzHGBCELf2OMCUIW/sYYE4Qs/I0xJghZ+BtjTBCy8DfGmCBk4W+MMUHIwt8YY4JQqNMFHE18fLy2a9euzvspKTlQ7fbQ0CZ13rcxxvhaampqlqom1NTOb8O/Xbt2pKSk1Hk/WVkfVbs9Pv7iOu/bGGN8TUS2H087G/YxxpggZOFvjDFByMLfGGOCkN+O+RtjAkNxcTEZGRkUFBQ4XUpAiYyMJDk5mbCwsFo938LfGFOnMjIyiImJoV27doiI0+UEBFUlOzubjIwM2rdvX6vX8Mmwj4i8KiJ7RWTtUR4XEXlBRNJEZI2I9PNFv8YY/1dQUEBcXJwFvw+JCHFxcV79NeWrMf/XgeHHePwCoFP5v/HAP3zUrzGmAbDg9z1vv6Y+GfZR1a9FpN0xmowC3tSyNSOXikhTEUlU1V2+6N/4r/15RWzPzuOn/fnsPlBATl4R2YeLOJhfTEFxKQXFHopKPIhAiAihLuGhEd3o2ioWgGVbstmadRh3u+Z0bNHY4XdjTOCorzH/JGBHpfsZ5duOCH8RGU/ZXwa0adOmnkozvvJ9xgFSt+/jwl6JtIiJBOCJTzYya/mOGp55pIJiT8XtOat38vaydB4b1aMi/L/enMmMRVvplhhLt8QYeic3pW1clO1dmhM2ZMgQpkyZgtvtPmqbyZMn8/vf/77ax959910efvhhWrVqxdNPP82bb77JCy+8UFfl+lR9hX91v5W/WDleVacD0wHcbretLO/HDheWkLI9h8Ed43GFlH17J8/bwJIt2SQ3i2JY97Lw79Qyhu6JsSQ1a0Rik0iaR4cTFx1ObKMwGoW5aBTuIswVgmrZQaxij3JyQnRFP+52zSgs8dAtMbZi24r0HBZuzmTh5syKbXHR4fRt04zTOjRncKd4urSMsQ8D4xPHCv8ZM2bw4osvMnToUIBjfoiciJKSEkJD6zae6yv8M4DWle4nAzvrqW/jI+nZeXyxcQ9fbtzL0i3ZFJcqH00YzCnJZfMgndejJcnNGtEyNrLiOTcPbs/Ng2t3NgLA6L7JjO6bfMS2cae2oWurGNbvOsT6nQdZtSOHrNwiPt+wh8837AEgISaCszoncF73lvyqUwKNwl21rsE0bNu2bWP48OEMHDiQlStX0rlzZ958802ioqKOaDdz5kwmT56MqjJixAiefPJJJk2aRH5+Pn369KFHjx68/fbbFe0fe+wxFi1axNatWxk5ciQjRoxgypQpzJ07l8zMTK666iqys7M59dRT+fTTT0lNTSU3N5eLLrqItWvLzo2ZMmUKubm5PPLIIwwZMoQzzjiDxYsXM3LkSK677jpuvfVW0tPTAXjuuecYNGiQz74u9RX+c4AJIjILGAgcsPH+hiEjJ4+P1+ziozU7WfvTwYrtIQK9k5uQV1RSse3GQbUP+RPRqkkkw5skMrxnIlD2F0P6vjxStuWw+McsFv2Qxd5DhbyXmsF7qRlEhoUw945f2TEDP9Fu0scn1L5nUixz7/jVL56/7YkRx/0amzZtYsaMGQwaNIibbrqJF198kfvuu6/i8Z07d/LAAw+QmppKs2bNOO+88/j3v//NE088wdSpU1m1atUvXvPhhx/myy+/rBg2+uqrryoee/TRRzn77LN58MEH+fTTT5k+ffpx1bl//34WLlwIwFVXXcU999zD4MGDSU9P5/zzz2fDhg3H/Z5r4pPwF5GZwBAgXkQygD8BYQCq+hIwD7gQSAPygBt90a+pG/lFpXyydhfvpmSwZEt2xfbGEaGc1SWBYd1acFbnFjSPDnewyv8REdrGRdM2LprL+iejqmzek8vnG/Ywf/0esnML6RD/v6Gk1xdvpXfrpvRp3dSGhoJE69atK/aar7nmGl544YUjwn/58uUMGTKEhISyyTCvvvpqvv76ay655JJa9bdo0SI+/PBDAIYPH06zZs2O63ljx46tuP3555+zfv36ivsHDx7k0KFDxMTE1Kqmqnx1ts+VNTyuwG990ZepOzmHi3j+ix94PzWDQ4Vle/SRYSEM69aSi3qdxJAuCUSG+f/wiYjQpVUMXVrF8NuhHckvKiWk/LjErgP5PDZ3Pa4QYdnvh/nNB1gwOZE9dl89v+qHfNX7ZRHlO0d7vdDQUDye/53QUPU8/ejo/+2keDwelixZQqNGjXxa289sbh9TITLMxQcryoK/b5umTB59Ct89NIypV/VjeM9WDSL4q1N5vN8VItw8uD1j3K0rgt/jUaZ++QM/7c93qkRTx9LT01myZAlQNrY/ePDgIx4fOHAgCxcuJCsri9LSUmbOnMlZZ50FQFhYGMXFxSfU3+DBg5k9ezYA8+fPJycnB4CWLVuyd+9esrOzKSwsZO7cuUd9jfPOO4+pU6dW3K9u6MkbFv5ByuNRPlq9k2teWVYxbt8o3MUTl/Vi3p2/4sPbB3HVwDbERtZu3hB/1SImkodGdOcvo0+p2Pblxr1Mmb+Zs55awL2zV5O2N9fBCk1d6NatG2+88Qa9evVi37593HbbbUc8npiYyF//+leGDh1K79696devH6NGjQJg/Pjx9OrVi6uvvvq4+/vTn/7E/Pnz6devH5988gmJiYnExMQQFhbGww8/zMCBA7nooovo2rXrUV/jhRdeICUlhV69etG9e3deeuml2r35oxBf/7njK263W20xl7qjqoyatpg1GQd4/JKeXHtaW6dLcsym3YeYtiCNj7/fRalHEYELeyZy97BOdGrpm/HVYLZhwwa6devmWP/btm074gyb+lBYWIjL5SI0NJQlS5Zw2223+XzPHar/2opIqqrWeM6pTewWJFSVz9btpmurWNrFRyMiTLqgK1uzDnNZv+SaXyCAdWkVwwtX9uW+87rw0tc/8l5KBh9/v4t5a3cxuk8Sdw3rRNu46JpfyJhy6enpjBkzBo/HQ3h4OC+//LLTJf2C7fkHwZ5/6vZ9TJ63kdTtOVzaN4m/je3jdEl+bfeBAqYtSGPmd+mUeJTQEOHa09ty1zmdaBplB4hPlNN7/oHMmz1/G/MPYD/tz+e3b6/gsn8sIXV7DnHR4fRre3ynnAWzVk0iefySniy4bwiX9kuiVJXXFm/jrKe/4pVvtlBc6qn5RcwR/HUnsyHz9mtqwz4BqKC4lH8u3MI/FqZRUOwhMiyE8b/qwPizTqZxhH3Lj1fr5lH8bUwfbh7cnsnzNrA4LZs/f7yBwhIPvx3a0enyGozIyEiys7NtWmcf+nk+/8jIyJobH4UlQYD55odMHvpwLen78gC4qFciv7+wGyc1rZtzhYNBj5Oa8NbNA/ly416mf72F689oV/GYqlqg1SA5OZmMjAwyMzNrbmyO288redWWhX+AyMot5PG56/nPqrIpk7q0jOHRUT04rUOcw5UFBhHhnG4tOadby4pteUUlXPHSEq47vS1j3K3tQ+AowsLCar3alKk7Fv4NnKry0Zpd/Ok/a8nJKyYyLIS7zunMLb9qT5jLDunUpX+v3Mm6nQd549vtXNovmTCXhb9pOCz8A8CcVTvJyStmcMd4Jo8+hTZxUTU/yXjtygGtiY5w0SG+ccUHbX5RKRGhIRXTSRjjryz8G6iC4lIiw1yICJNH9+Tc7i1s6KGeiQij+iQdse3+99eQc7iIpy7vZcdZjF+zcYEG5nBhCQ9+sIYrX15KSfkphy1iIxl7ahsLfoftOVjAoh8yWZSWxQXPf8O8723WcuO/LPwbmJJS5atNmazbeZA1Px1wuhxTScvYSObfcxZnd23Bgfxibn97BQ+8t+aINQ+M8RcW/g2AqlLqKbugo0lUGFOv6secCYPo18Yu2PI3CTERzLjezaMjexAeGsI7KTsYOXUxm/cccro0Y45g4e/nDhWU7UE+9enGim392zaja6vYYzzLOElEuP6MdsyZMIiOLRqTtjeXUVMX815qhtOlGVPBwt+Pbd5ziFFTF/PJ2t3833fpZOUWOl2SOQFdW8UyZ8IgLu2bRH5xKfe9u5pJ76+hoLjU6dKMsfD3V3NW72TU1MVsyTpM11YxfDRhMPGNI5wuy5ygqPBQnhnTm6cu60VEaAizlu9g7PSl7LSFY4zDLPz9TKlH+eu8Ddw5cyX5xaWM7pvEh7cPol28TSncUIkIY05tzfu3nUFS00as3rGfMf9cQlGJTRBnnGPn+fuRA/nF3DVrJV9tyiQ0RPjjRd257vS2dgpngOiZ1IS5dwzmzlkrucLdmvBQ2/cyzvFJ+IvIcOB5wAW8oqpPVHm8DfAG0LS8zSRVneeLvgPF1qzD3Pz6crZkHaZZVBgvXt2f00+2eXkCTbPocN68acARH+ird+ynx0mxhNp0HKYeef3TJiIuYBpwAdAduFJEuldp9gdgtqr2BcYBL3rbbyBZuiWb0S/+b3x/zoTBFvwBrGrwj/nnEm58fbkdCDb1yhd7/gOANFXdAiAis4BRwPpKbRT4+dzEJsBOH/QbEN5PzWDSB2soLlXO7tqCF67sa3PuB5ESjxITGUpS00ZE2DCQqUe+SJkkYEel+xnAwCptHgHmi8gdQDQwzAf9BoQ9hwooLlVuGtSeh0Z0w2UTggWV/m2b8dEdZWdy/fwXga0RYOqDL3Y1qvsprbq+2JXA66qaDFwI/EtEftG3iIwXkRQRSQmWhR9uO+tk3r5lIA9f3N2CP0glNmlUMSvogbxiRr/4LV9t2utwVSbQ+SL8M4DWle4n88thnZuB2QCqugSIBOKrvpCqTldVt6q6ExISfFCa/8krKuF3764mI6dspS0RYVDHX3wpTJCauTydVTv2c8sbKbxvVwSbOuSL8F8OdBKR9iISTtkB3TlV2qQD5wCISDfKwj84du2reOrTTbybmsHEd1bbotbmF35zZgduG3IyJR7l3ndX84+vfrSfE1MnvB7zV9USEZkAfEbZaZyvquo6EXkMSFHVOcC9wMsicg9lQ0I3aJD+RN9zbmcycvJ58MKuNq5rfkFEeGB4V1rERPDY3PU8+elG9ucVMekC+3kxviX+msFut1tTUlLqvJ+srI+q3R4ff7HP+th1IJ8WMZE2pm9OyJzVO5n4zipKPMpYd2smX3qK/QyZGolIqqq6a2pn55bVsU27D3Hx3xfzwPtr8Hj884PW+KeRvU/i5evcRJRPDX3HzBU2JYTxGQv/OvR9xgHGTl9CVm4hO/fnU1Rqv7jmxAzt2oJ/3TyQmIhQ5n2/m1vfSrWLwYxPWPjXkdTt+7jq5aXszyvm7K4tePWGU4kMczldlmmABrRvzszxp9E0KowvN+7lljdSbHUw4zUL/zrw3dZ9XDfjOw4VljDilEReuqa/Bb/xSs+kJswafxrxjcNZlJbFbW+tsLOAjFcs/H1s6ZZsbnjtOw4XlXJJn5N4flwfm73R+ETXVrHMGn867eKiGH9mBzv7x3jFJpHxoW9/zOLm11PILy7l0n5JPH15bzs7w/hUxxaN+XziWUfMAGrTQZjasF1SH1m6Jbsi+K/on2zBb+pM5eBfsHEvV7+yjNxCOwZgToyFvw8s37aPm15fTn5xKZf3T+bJy3pZ8Js6V1zq4dGP1vHtj9nMXr6j5icYU4kN+3hp94ECbnxtOXlFpVzaN4knL+tFiAW/qQdhrhDeuGkAH678iRsHtXO6HNPAWPh7qVWTSG4bcjKb9xzi6StsqMfUr7Zx0dw9rHPF/f15RTQKdxERameXmWOz8K+lygfZfju0ox10M47Lyi3kmleW0S4umqlX9bVlIc0x2U9HLWzPPswVLy0hPTuvYpsFv3Haz1eSf7puN/fbdCKmBhb+tfDEJxtJ2Z7DM//d5HQpxlTo2iqW124cQFS4iw9W/MQjH62zC8HMUVn418JTl/fixkHt+MvoU5wuxZgj9G/bjJevcxPuCuHNJdt5Zv5mp0syfsrC/zjlF5VW/BkdExnGny7uYQutG780qGM8067uhytEmLogjRmLtjpdkvFDFv7HoajEw6/fTGHi7FUU28ycpgE4t3tLnrysFwCPz13PBytsSUhzJAv/GnjKl9NblJbForQs9h4qdLokY47L5f2TeejCbgD87r01LNhoi8Kb/7HwPwZV5fGP1/PR6p00jgjl9RsHkNS0kdNlGXPcfl2+JnCpR7n97RWsTM9xuiTjJyz8j+GlhVt4bfE2wlzC9Gv70zOpidMlGXPC7j+/C5f3Tya/uJSbXl/Olsxcp0syfsDC/yg+XJnBk59uRASeHduHMzrGO12SMbUiIvz10lMY2iWBohIPuw8UOF2S8QM+OV1FRIYDzwMu4BVVfaKaNmOARwAFVqvqVb7ouy58tx3u/2ANAH8c0Z2Lep3kcEXGeCfMFcK0q/uRvi+Prq1inS7H+AGvw19EXMA04FwgA1guInNUdX2lNp2AB4FBqpojIi287beu/JAJv/uPUFyq3DK4PTcNbu90Scb4RFR46BHBvyZjP90TY20aiCDli+/6ACBNVbeoahEwCxhVpc2vgWmqmgOgqn552sHeQ3DX+8LhImHEKYn8vvxMCWMCzX9W/cSlL37LH/9jVwEHK1+EfxJQeTLxjPJtlXUGOovIYhFZWj5M5FcOF8HdHwp7c4XeScozY3rb1MwmYCU3a0RIiNA4woVlf3DyxZh/dQlZ9ccpFOgEDAGSgW9EpKeq7j/ihUTGA+MB2rRp44PSjt83P8LmvULrpsozo9QWXDcBrX/b5vz3njNpGxftdCnGIb4I/wygdaX7ycDOatosVdViYKuIbKLsw2B55UaqOh2YDuB2u+t1f2R4N1D10CMRmkbVZ8/GOKNy8GflFrL7QIGdzhxEfDHssxzoJCLtRSQcGAfMqdLm38BQABGJp2wYaIsP+vZaUaWlTy/oDm2aOVeLMU7YuT+fS6Yt5obXvmPHvryan2ACgtfhr6olwATgM2ADMFtV14nIYyIysrzZZ0C2iKwHFgC/U9Vsb/v21oJNe7nsVWHjHqcrMcY5CTERtI+PJiu3iJvfWM6hgmKnSzL1wCfneKnqPFXtrKonq+pfyrc9rKpzym+rqk5U1e6qeoqqzvJFv95689tt7DooLPKLv0GMccbP1wB0bNGYzXtyuXPmSkptIZiAF9Qn+L50bX8mDfNw02lOV2KMs2Ijw5hxvZtmUWEs2JTJ5HkbnC7J1LGgC//iUk/FXk1EqIvL+4Cd0WlM2QHgl67pT5hLmLFoKzO/S3e6JFOHgir8VZU/fLiWX7+ZYuOaxlRjYIe4ihXq/vjvtSzb4vihOVNHgir8X1u8jXdSdvDtj1lsz7azGoypzhh3a24Z3J4Sj3Lb2yvIyLHflUAUNOH/zQ+Z/PnjsumGnr68t53PbMwxTLqgK2d2TmDf4SJueSOFw4UlNT/JNChBEf7bsw8z4f9W4lGYMLQjF/e2WTqNOZZQVwh/v7IvHeKj2bj7EPfOXl2xhrUJDAEf/rmFJfz6zRQO5BczrFsLJp7b2emSjGkQmjQK4+Xr3cREhrJsazYZOflOl2R8yCfz+fsrj0eZ+M4qNu/JpWOLxjw7to9N1mbMCTg5oTH/vLY/rZtF0bq5zXsSSAI6/KcuSGP++j3ERoby8nVuYiLDnC7JmAbnjJOPXMWusKSUiFCb+LChC9hhny827OHZzzcjAs9f2Zf28TZ7oTHeUFVeWvgjI15YxEE7VbrBC8jw35KZy92zVqEK953XhaFd/HbhMGMajMISD/9e+RNpe3NZuCnT6XKMlwJu2Kek1MNtb63gUGEJw3u04vYhJztdkjEBITLMxT+v7c/mPbmc272l0+UYLwXcnn+oK4T7h3ehf9tmTBnTGxE7wGuMr7SNiz4i+O30z4Yr4MIf4JxuLXnv1tNpHBFwf9gY4zdSt+/j/Oe+Jt2ulm+QAjL8AdvjN6aOzVi0lR/25nLrW6kUFJc6XY45QQEb/saYuvXXS3vRLi6K9bsO8tCHa1FbCb5BsfA3xtRKk0Zh/OOa/kSGhfD+igz+z6aAblAs/I0xtdYtMZa/Xlo2BfQjc9axesd+hysyx8vC3xjjldF9k7n2tLYUlyq3v72CnMNFTpdkjoOFvzHGa3+4qBu9Wzflp/35TJy9yk4BbQB8Ev4iMlxENolImohMOka7y0VERcTti36NMf4hItTFtKv60rR8DeAXv0pzuiRTA6/DX0RcwDTgAqA7cKWIdK+mXQxwJ7DM2z6NMf4nuVkUz43tgwj87b+b+TYty+mSzDH4Ys9/AJCmqltUtQiYBYyqpt3jwFNAgQ/6NMb4oSFdWnDH0I54FO6ctYq9B+3X3V/5IvyTgB2V7meUb6sgIn2B1qo61wf9GWP82F3DOnN6hzjaxkVhQ//+yxfzH1R3KW3Ft1xEQoBngRtqfCGR8cB4gDZt2vigNGNMfXOFCC9d05+oCBdhLjunxF/54juTAbSudD8Z2FnpfgzQE/hKRLYBpwFzqjvoq6rTVdWtqu6EhAQflGaMcUKTqLCK4Pd4lO3Zhx2uyFTli/BfDnQSkfYiEg6MA+b8/KCqHlDVeFVtp6rtgKXASFVN8UHfxhg/lltYwo2vL2f0i9+y+4CN//sTr8NfVUuACcBnwAZgtqquE5HHRGSkt69vjGm4GoW5KPUoqsqOHJv905/4ZM5jVZ0HzKuy7eGjtB3iiz6NMf7PFSI8N64PRSUeTmrayOlyTCU24b0xpk7FN4444n5eUQlR4RY9TrND8caYeuHxKC9+lcbZUxaSeajQ6XKCnoW/MaZeKPD15kx2Hyyw+X/8gIW/MaZeuEKE58f1JS46nG9+yOIfC390uqSgZuFvjKk3LWMjeWZMb6Bs/p/U7fscrih4WfgbY+rVkC4t+M2ZHSj1KHfOXMWBvGKnSwpKFv7GmHp33/ldKub/n/TBGlv/1wEW/saYehfmCuHv4/oSExHKJ2t38/YyW/+3vln4G2Mc0SYuir+Ur//7+Nz1bNx90OGKgouFvzHGMSN7n8QYdzKFJR7unLmSguJSp0sKGhb+xhhHPTKyBx0Sotm8J5c/f7ze6XKChoW/McZRUeGhvDCuL+GhIUSHh9rB33piE2wYYxzXM6kJX/9uKK2aRDpdStCwPX9jjF+oHPwH8ooptekf6pSFvzHGryzbks35z33NSzb9Q52y8DfG+JX84lJ2Hyxg4aZM2/uvQzbmb4zxK0O6tOC1G0/lVx3jcYWI0+UELAt/Y4zfGdqlRcVtVUXEPgR8zYZ9jDF+K/NQITe9vpy5a3Y6XUrAsT1/Y4zf+mLDHhZsyiR1ew592zQjydYB9hnb8zfG+K2xp7ZmWLcWHCwoYeI7q+wAsA/5JPxFZLiIbBKRNBGZVM3jE0VkvYisEZEvRKStL/o1xgQ2EeHJy3qREBPBsq377PRPH/I6/EXEBUwDLgC6A1eKSPcqzVYCblXtBbwHPOVtv8aY4BDXOIJnrihb/evZ/25mTcZ+hysKDL7Y8x8ApKnqFlUtAmYBoyo3UNUFqppXfncpkOyDfo0xQeLMzgncOKgdJR7l7lmryCsqcbqkBs8X4Z8E7Kh0P6N829HcDHxS3QMiMl5EUkQkJTMz0welGWMCxQPDu9K5ZWO2ZB3m8bkbnC6nwfNF+Fd3Am61R2VE5BrADTxd3eOqOl1V3arqTkhI8EFpxphAERnm4vlxfQl3hTDzu3Tmr9vtdEkNmi/CPwNoXel+MvCLk3JFZBjwEDBSVQt90K8xJsh0S4zl/uFdAJj0wffsPVTgcEUNly/CfznQSUTai0g4MA6YU7mBiPQF/klZ8O/1QZ/GmCB106D2DO4Yz77DRdz/ni3+XlteX+SlqiUiMgH4DHABr6rqOhF5DEhR1TmUDfM0Bt4tv0w7XVVHetu3L8THX+x0CcaYExASIky5ojfnP/c1q3bsJ31fHm3jop0uq8ERf/3UdLvdmpKS4nQZxhg/tXRLNu3jo2kZawvAVCYiqarqrqmdTe9gjGmQTusQ53QJDZpN72CMadBKPcq0BWn87b+bnS6lQbE9f2NMg7Zh10Gemb8JEeGK/sm0bh7ldEkNgoW/MaZB65nUhEkXdKVrq1gL/hNg4W+MafDGn3my0yU0ODbmb4wJKN9t3ceCjXY5UU0s/I0xASN1ew5jpy9h4uxV7D1oV/8ei4W/MSZg9G3dlMEd48nJK+Z3dvXvMVn4G2MCxs9X/zZpFMbCzZn8a+l2p0vyWxb+xpiA0jI2ksmjTwFg8rwN/JiZ63BF/snC3xgTcEb0SuTSvkkUFHuY+M4qiks9Tpfkdyz8jTEB6ZFRPUhq2ojVGQeY+mWa0+X4HQt/Y0xAio0MY8oVvRGBqQvSWJme43RJfsXC3xgTsE4/OY5bBren1KNMnL3a1v6txMLfGBPQ7j2vC11axrA16zCT59navz+z8DfGBLTIMBfPju1DmEt4a2k6S7dkO12SX7C5fYwxAa/7SbHcf35XDheV0L9tM6fL8QsW/saYoPDrMzs4XYJfsWEfY0zQycot5Nsfs5wuw1EW/saYoLJzfz7nP/s1v3kzlZ/25ztdjmN8Ev4iMlxENolImohMqubxCBF5p/zxZSLSzhf9GmPMiUpsEkm/ts3omdSEEHG6Gud4PeYvIi5gGnAukAEsF5E5qrq+UrObgRxV7Sgi44AngbHe9m2MMSdKRHhubB8ahbkICeL098We/wAgTVW3qGoRMAsYVaXNKOCN8tvvAeeISPB+1Y0xjoqOCK0Ifo9HycotdLii+ueL8E8CdlS6n1G+rdo2qloCHADifNC3McbU2t5DBVz9yjKunfEdRSXBNfmbL8K/uj34qisoHE8bRGS8iKSISEpmZqYPSjPGmKOLCg8lY38eG3Yd5LnPNztdTr3yRfjpDGGxAAAKTUlEQVRnAK0r3U8Gdh6tjYiEAk2AfVVfSFWnq6pbVd0JCQk+KM0YY46ucUQoz47pQ4jASwt/JGXbL2IpYPki/JcDnUSkvYiEA+OAOVXazAGuL799OfCl2vpqxhg/4G7XnN+cdTIehYmzV5NbGByTv3kd/uVj+BOAz4ANwGxVXScij4nIyPJmM4A4EUkDJgK/OB3UGGOccs+wznRLjCV9Xx5/+Xh9zU8IAOKvO+But1tTUlKcLsMYEyQ27T7ExX9fRFGph1euczOse0unS6oVEUlVVXdN7ewKX2OMAbq0iuH+4V0AmPTBGrID/PRPC39jjCl306D2nNahOVm5RTz4wff468iIL1j4G2NMuZAQYcoVvYmJCGX++j28m5LhdEl1xsLfGGMqSW4WxaOjegDw6Efr2LEvz+GK6oaFvzHGVDG6bxIXntKKqIhQ9hwscLqcOmGLuRhjTBUiwuTRp+BRaB4d7nQ5dcLC3xhjqtE06sjQLywpJSLU5VA1vmfDPsYYcwxFJR6e/mwjo6YupqC41OlyfMbC3xhjjqHUo3zy/W427TkUUEs/2rCPMcYcQ6NwF8+P60tBSSmntmvudDk+Y+FvjDE1OCW5idMl+JwN+xhjzAlYuDmTxz5q+JO/2Z6/McYcp5zDRdz+ViqHi0rp06YpI3uf5HRJtWZ7/sYYc5yaRYfz0IjuAPzhw+/ZuT/f4Ypqz8LfGGNOwJUDWnNO1xYcLCjhvndX4/E0zMnfLPyNMeYEiAhPXNaLuOhwvv0xm1cXb3W6pFqx8DfGmBOUEBPBE5f1AuCpzzaxcfdBhys6cRb+xhhTC+d2b8mVA9pQVOLh7lmrGtzVvxb+xhhTS38Y0Y12cVFs3H2IZ+ZvcrqcE2Lhb4wxtRQdEcqzY/vgChFe/mYri9MazvQPXoW/iDQXkf+KyA/l/zerpk0fEVkiIutEZI2IjPWmT2OM8Sd92zTjzrM7AXDv7NXszytyuKLj4+2e/yTgC1XtBHxRfr+qPOA6Ve0BDAeeE5GmXvZrjDF+47dDT6Zfm6bsPljAv5Zsd7qc4+LtFb6jgCHlt98AvgIeqNxAVTdXur1TRPYCCcB+L/s2xhi/EOoK4dmxfZi/bg83D27vdDnHxdvwb6mquwBUdZeItDhWYxEZAIQDP3rZrzHG+JW2cdH8+swOTpdx3Goc9hGRz0VkbTX/Rp1IRyKSCPwLuFFVPUdpM15EUkQkJTMz80Re3hhj/MbO/fk8Pnc9JaXVRp1fqHHPX1WHHe0xEdkjIonle/2JwN6jtIsFPgb+oKpLj9HXdGA6gNvtbpjXTBtjgpqqctPry9m4+xDxjSO4bcjJTpdULW8P+M4Bri+/fT3wn6oNRCQc+BB4U1Xf9bI/Y4zxayLCwxd1Z1i3FlzhTna6nKPydsz/CWC2iNwMpANXAIiIG7hVVW8BxgBnAnEickP5825Q1VVe9m2MMX7pjI7xnNEx3ukyjklU/XN0xe12a0pKitNlGGOMV0pKPXy+YQ/DeybWS38ikqqq7pra2RW+xhhTR1SV61/7jlvfWsGc1TudLucIFv7GGFNHRIQLTynb43/ow+/JyMlzuKL/sfA3xpg6dNWANpzbvSWHCkq4e9Yqvzn908LfGGPqkIjw5GW9aBETQcr2HKYt8I9rXC38jTGmjjWPDufZsX0Qgee/2EzKtn1Ol2Thb4wx9WFQx3jGn9kBj8Jds1ZxIL/Y0Xos/I0xpp7ce24XeiU34af9+Tz04fc4eaq9hb8xxtST8NAQnh/Xl6hwF3PX7OLd1AzHarHwN8aYetQ+PprHRvUE4JE56/gxM9eROiz8jTGmnl3WL4lRfU4ir6iUe95ZhcdT/8M/3s7tY4wx5gSJCH++pCd7DhYw8dwuhIRIvddg4W+MMQ6IiQxj1vjTHevfhn2MMcYPfLVpL7sPFNRbfxb+xhjjsNkpO7jhteXcNWslpfU0/m/hb4wxDhvapQWJTSI5q0sC9TX6b2P+xhjjsISYCL68dwiNwl311qft+RtjjB+oz+AHC39jjAlKFv7GGBOELPyNMSYIeRX+ItJcRP4rIj+U/9/sGG1jReQnEZnqTZ/GGGO85+2e/yTgC1XtBHxRfv9oHgcWetmfMcYYH/A2/EcBb5TffgO4pLpGItIfaAnM97I/Y4wxPuBt+LdU1V0A5f+3qNpAREKAZ4DfedmXMcYYH6nxIi8R+RxoVc1DDx1nH7cD81R1h8ixr10TkfHAeIA2bdoc58sbY4w5UTWGv6oOO9pjIrJHRBJVdZeIJAJ7q2l2OvArEbkdaAyEi0iuqv7i+ICqTgemA7jdbufWNzPGmADn7fQOc4DrgSfK//9P1QaqevXPt0XkBsBdXfAbY4ypP+LNAsIiEgfMBtoA6cAVqrpPRNzArap6S5X2N1AW/hOO47Uzge21KCseyKrF8xoye8/BIxjft73nE9NWVRNqauRV+PsjEUlRVbfTddQne8/BIxjft73numFX+BpjTBCy8DfGmCAUiOE/3ekCHGDvOXgE4/u291wHAm7M3xhjTM0Ccc/fGGNMDQIq/EVkuIhsEpE0EQn4awlEpLWILBCRDSKyTkTucrqm+iIiLhFZKSJzna6lPohIUxF5T0Q2ln+/T3e6promIveU/1yvFZGZIhLpdE11QUReFZG9IrK20rbjnjG5tgIm/EXEBUwDLgC6A1eKSHdnq6pzJcC9qtoNOA34bRC855/dBWxwuoh69Dzwqap2BXoT4O9dRJKAOym7Lqgn4ALGOVtVnXkdGF5l24nMmFwrARP+wAAgTVW3qGoRMIuyWUcDlqruUtUV5bcPURYISc5WVfdEJBkYAbzidC31QURigTOBGQCqWqSq+52tql6EAo1EJBSIAnY6XE+dUNWvgX1VNh/XjMneCKTwTwJ2VLqfQRAE4c9EpB3QF1jmbCX14jngfsDjdCH1pAOQCbxWPtT1iohEO11UXVLVn4AplM0csAs4oKrBNCV8jTMmeyuQwr+6KUOD4lQmEWkMvA/craoHna6nLonIRcBeVU11upZ6FAr0A/6hqn2Bw9TBMIA/KR/jHgW0B04CokXkGmerCiyBFP4ZQOtK95MJ0D8TKxORMMqC/21V/cDpeurBIGCkiGyjbGjvbBF5y9mS6lwGkKGqP/9V9x5lHwaBbBiwVVUzVbUY+AA4w+Ga6tOe8pmSOcaMyV4JpPBfDnQSkfYiEk7ZwaE5DtdUp6RsgYQZwAZV/ZvT9dQHVX1QVZNVtR1l3+MvVTWg9whVdTewQ0S6lG86B1jvYEn1IR04TUSiyn/OzyHAD3JX8fOMyXCUGZO95e2Uzn5DVUtEZALwGWVnBryqquscLquuDQKuBb4XkVXl236vqvMcrMnUjTuAt8t3bLYANzpcT51S1WUi8h6wgrKz2lYSoFf6ishMYAgQLyIZwJ8omyZ/tojcTPmMyT7v167wNcaY4BNIwz7GGGOOk4W/McYEIQt/Y4wJQhb+xhgThCz8jTEmCFn4G2NMELLwN8aYIGThb4wxQej/AbOPulJA2Li4AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## axvspan 竖直参考区域\n",
    "plt.plot(x, y, \n",
    "\tls='-.', # 折线图的线条风格\n",
    " \tlw=2,   # 折线图的线宽\n",
    " \tlabel='plot figure')\n",
    "\n",
    "plt.legend()\n",
    "plt.axvspan(xmin=0.4, # 起始位置\n",
    "\t\t\txmax=0.6,\t# 终止位置\n",
    "\t\t\tymin=0.4,\n",
    "\t\t\tymax=1,\n",
    "\t\t\tfacecolor='y', # 填充颜色\n",
    "\t\t\talpha=0.3) # 填充透明度\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## axvspan 竖直参考区域\n",
    "plt.plot(x, y, \n",
    "\tls='-.', # 折线图的线条风格\n",
    " \tlw=2,   # 折线图的线宽\n",
    " \tlabel='plot figure')\n",
    "\n",
    "plt.legend()\n",
    "plt.axhspan(ymin=0,ymax=0.6,xmin=0,xmax=1,facecolor='g',alpha=0.3)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## annotate 添加指向性注释文本\n",
    "\n",
    "Annotate the point ``xy`` with text ``s``.\n",
    "\n",
    "Additional kwargs are passed to `~matplotlib.text.Text`.\n",
    "\n",
    "Parameters\n",
    "----------\n",
    "\n",
    "s : str\n",
    "    The text of the annotation\n",
    "\n",
    "xy : iterable\n",
    "    Length 2 sequence specifying the *(x,y)* point to annotate\n",
    "\n",
    "xytext : iterable, optional\n",
    "    Length 2 sequence specifying the *(x,y)* to place the text\n",
    "    at.  If None, defaults to ``xy``.\n",
    "\n",
    "xycoords : str, Artist, Transform, callable or tuple, optional\n",
    "\n",
    "    The coordinate system that ``xy`` is given in.\n",
    "\n",
    "    For a `str` the allowed values are:\n",
    "\n",
    "    =================   ===============================================\n",
    "    Property            Description\n",
    "    =================   ===============================================\n",
    "    'figure points'     points from the lower left of the figure\n",
    "    'figure pixels'     pixels from the lower left of the figure\n",
    "    'figure fraction'   fraction of figure from lower left\n",
    "    'axes points'       points from lower left corner of axes\n",
    "    'axes pixels'       pixels from lower left corner of axes\n",
    "    'axes fraction'     fraction of axes from lower left\n",
    "    'data'              use the coordinate system of the object being\n",
    "                        annotated (default)\n",
    "    'polar'             *(theta,r)* if not native 'data' coordinates\n",
    "    =================   ===============================================\n",
    "\n",
    "    If a `~matplotlib.artist.Artist` object is passed in the units are\n",
    "    fraction if it's bounding box.\n",
    "\n",
    "    If a `~matplotlib.transforms.Transform` object is passed\n",
    "    in use that to transform ``xy`` to screen coordinates\n",
    "\n",
    "    If a callable it must take a\n",
    "    `~matplotlib.backend_bases.RendererBase` object as input\n",
    "    and return a `~matplotlib.transforms.Transform` or\n",
    "    `~matplotlib.transforms.Bbox` object\n",
    "\n",
    "    If a `tuple` must be length 2 tuple of str, `Artist`,\n",
    "    `Transform` or callable objects.  The first transform is\n",
    "    used for the *x* coordinate and the second for *y*.\n",
    "\n",
    "    See :ref:`plotting-guide-annotation` for more details.\n",
    "\n",
    "    Defaults to ``'data'``\n",
    "\n",
    "textcoords : str, `Artist`, `Transform`, callable or tuple, optional\n",
    "    The coordinate system that ``xytext`` is given, which\n",
    "    may be different than the coordinate system used for\n",
    "    ``xy``.\n",
    "\n",
    "    All ``xycoords`` values are valid as well as the following\n",
    "    strings:\n",
    "\n",
    "    =================   =========================================\n",
    "    Property            Description\n",
    "    =================   =========================================\n",
    "    'offset points'     offset (in points) from the *xy* value\n",
    "    'offset pixels'     offset (in pixels) from the *xy* value\n",
    "    =================   =========================================\n",
    "\n",
    "    defaults to the input of ``xycoords``\n",
    "\n",
    "arrowprops : dict, optional\n",
    "    If not None, properties used to draw a\n",
    "    `~matplotlib.patches.FancyArrowPatch` arrow between ``xy`` and\n",
    "    ``xytext``.\n",
    "\n",
    "    If `arrowprops` does not contain the key ``'arrowstyle'`` the\n",
    "    allowed keys are:\n",
    "\n",
    "    ==========   ======================================================\n",
    "    Key          Description\n",
    "    ==========   ======================================================\n",
    "    width        the width of the arrow in points\n",
    "    headwidth    the width of the base of the arrow head in points\n",
    "    headlength   the length of the arrow head in points\n",
    "    shrink       fraction of total length to 'shrink' from both ends\n",
    "    ?            any key to :class:`matplotlib.patches.FancyArrowPatch`\n",
    "    ==========   ======================================================\n",
    "\n",
    "    If the `arrowprops` contains the key ``'arrowstyle'`` the\n",
    "    above keys are forbidden.  The allowed values of\n",
    "    ``'arrowstyle'`` are:\n",
    "\n",
    "    ============   =============================================\n",
    "    Name           Attrs\n",
    "    ============   =============================================\n",
    "    ``'-'``        None\n",
    "    ``'->'``       head_length=0.4,head_width=0.2\n",
    "    ``'-['``       widthB=1.0,lengthB=0.2,angleB=None\n",
    "    ``'|-|'``      widthA=1.0,widthB=1.0\n",
    "    ``'-|>'``      head_length=0.4,head_width=0.2\n",
    "    ``'<-'``       head_length=0.4,head_width=0.2\n",
    "    ``'<->'``      head_length=0.4,head_width=0.2\n",
    "    ``'<|-'``      head_length=0.4,head_width=0.2\n",
    "    ``'<|-|>'``    head_length=0.4,head_width=0.2\n",
    "    ``'fancy'``    head_length=0.4,head_width=0.4,tail_width=0.4\n",
    "    ``'simple'``   head_length=0.5,head_width=0.5,tail_width=0.2\n",
    "    ``'wedge'``    tail_width=0.3,shrink_factor=0.5\n",
    "    ============   =============================================\n",
    "\n",
    "    Valid keys for `~matplotlib.patches.FancyArrowPatch` are:\n",
    "\n",
    "    ===============  ==================================================\n",
    "    Key              Description\n",
    "    ===============  ==================================================\n",
    "    arrowstyle       the arrow style\n",
    "    connectionstyle  the connection style\n",
    "    relpos           default is (0.5, 0.5)\n",
    "    patchA           default is bounding box of the text\n",
    "    patchB           default is None\n",
    "    shrinkA          default is 2 points\n",
    "    shrinkB          default is 2 points\n",
    "    mutation_scale   default is text size (in points)\n",
    "    mutation_aspect  default is 1.\n",
    "    ?                any key for :class:`matplotlib.patches.PathPatch`\n",
    "    ===============  ==================================================\n",
    "\n",
    "    Defaults to None\n",
    "\n",
    "annotation_clip : bool, optional\n",
    "    Controls the visibility of the annotation when it goes\n",
    "    outside the axes area.\n",
    "\n",
    "    If `True`, the annotation will only be drawn when the\n",
    "    ``xy`` is inside the axes. If `False`, the annotation will\n",
    "    always be drawn regardless of its position.\n",
    "\n",
    "    The default is `None`, which behave as `True` only if\n",
    "    *xycoords* is \"data\".\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(0.05, 10, 1000)\n",
    "y = np.sin(x)\n",
    "plt.plot(x, y, \n",
    "\tls='-.', # 折线图的线条风格\n",
    " \tlw=2,   # 折线图的线宽\n",
    " \tlabel='plot figure')\n",
    "plt.legend()\n",
    "\n",
    "plt.annotate(s='maximum', # 注释文本\n",
    "\t\t\txy=(np.pi/2, 1.0), # 被注释图像内容的位置坐标 （箭头指向的地方，即需要标注的坐标点）\n",
    "\t\t\txytext=((np.pi/2)+1.0, 0.8), # 注释文本的位置坐标（箭头开始指的地方，即放置注释文本的地方）\n",
    "\t\t\tcolor='b',\t# 注释文本的颜色\n",
    "\t\t\tarrowprops=dict(arrowstyle='->', connectionstyle='arc3',color='b')) # 箭头的属性字典\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYYAAAD8CAYAAABzTgP2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAIABJREFUeJzt3Xd4lHW2wPHvmfSEEBIILQkEpBN6ACkuTYoV13ZVdG27ll1X113rFvW6q7L3enddr7peK1gWC2tBRUFAlCYQepcAAUJLQkISCKnzu3/MBCeQkJAp75TzeZ55MvPOW85AMuf9dTHGoJRSStWyWR2AUkop/6KJQSmlVB2aGJRSStWhiUEppVQdmhiUUkrVoYlBKaVUHZoYlFJK1aGJQSmlVB2aGJRSStURbnUAzdGmTRuTnp5udRhKKRVQ1qxZU2CMSW5sv4BMDOnp6WRlZVkdhlJKBRQR2duU/bQqSSmlVB2aGJRSStWhiUEppVQdmhiUUkrVoYlBKaVUHR5JDCLyhojkicjmBt4XEXleRLJFZKOIDHZ572YR2el83OyJeELOzp2gCy4ppTzEUyWGGcCUs7x/EdDd+bgD+CeAiCQBjwPDgWHA4yKS6KGYgt/y5TByJPToAVu3Wh2NUipIeGQcgzHmOxFJP8suU4G3jGMd0e9FpJWIdADGAl8bYwoBRORrHAlmlifiCgafbTjInA0HOVlZQ3SEjbSkWCaW5TL8708QtmkjlJVBfDxUV1sdqlIeY7cb1uceY8kPBfyQV0rJySpsIqQlxdA/pRVTB3UkKjzM6jCDlq8GuKUA+11e5zq3NbT9DCJyB47SBp06dfJOlH6gpNzxB9AiyvFfc6j4JF9vPVJnny7zX2LEuu9/3FBaCgMH+jJMz0tMhMJCq6NQFqustvPhmv28/O0u9heerHefpLjDXDm43q8J5SG+SgxSzzZzlu1nbjTmFeAVgMzMzKCsUF+0/QgPfLiRacM78btJPQGY3Lc9Ka1iaRkTzvHyanbmHeeTTr/no+8n8Og3b9D/SDaRpgZZtRrboABODlLfr4IKJWv2FvHIvzeyM+84AB0TopnUtz39UxNo3SKKqmo7ewpOEB4mhIc5asErqmt4bckebhvVhZhILUF4iq8SQy6Q5vI6FTjo3D72tO2LfRST34mNDKfwRCWbDhRjjEFE6Nw6js6t407tcxFw74TubL2iH3/7+gIKFi7h9tWfsHBZPv/Zs4qE2AjrPoBSzWCM4Y1lOTz1xVbsBrq0ieOBST2ZktGeMNvZbxhe/GYXzy/cyao9hcy8bZiPIg5+YjzUm8XZxvC5MSajnvcuAe4BLsbR0Py8MWaYs/F5DVDbS2ktMKS2zaEhmZmZJljmSqpNALWycgoZ0jmxzraz+WrzYR6avYGS8mp6tovn7duH0bZltLfC9R4R7VkVorJyCrn65RUA/OKCLvxuUk+iI5p2978x9xgPzd7I01f2Y3An7bfSGBFZY4zJbGw/j5QYRGQWjjv/NiKSi6OnUQSAMeZlYC6OpJANlAG3Ot8rFJE/A6udp3qysaQQTErKq/jFzCx+Pb47o7u3ASAzPemczjEloz19O7bk1hmr+SGvlLX7ipiS0cEb4SrlFZnpSfx6fDd6tIvnsgEdz+nY/qmtmHvvBdhcShZFJypJjIv0dJghxWMlBl8KhhJDWWU1N72+ijV7i+jetgVf3nfBqXrT5ig8UcmKXUe5pH+AJgUtMYQUYwzHK6qJj/Zs1een6w/wp082894dI+jTsaVHzx0Mmlpi0JHPFrDbDb/7YANr9hbRMSGaN24Z6lZSAEiKi6yTFHIKTlBeVeNuqEp5xUuLd3Hp/y4l29nQ7CnfbM+jpLya22as5lBx/b2aVOM0MVjg+UU7+XLzYeKjwnnr9mGkJcV69Pzr9x/jpy8t47FP6x2IrpSlKqvtzNtymH2FZezK92ximH5Vf4amJ3K4pJxfvJWlN0fNpInBx777IZ/nFuzEJvD8DYPo1jbe49eIDLNRVlnDkZKKwPnD6NvX6giUj0SG23jvjvP5vxuHMLlve4+eOzoijFd/lklaUgybD5Tw9NxtHj1/qNDE4ENHj1fwuw83AHD/hT0Y17OtV67Tp2NLPvrlSN68ZWiTe3dYbrOWboKd3W6obdOMjQxnkoeTQq1WsZG8eMNgIsNsvLViL3M3HfLKdYKZJgYfMcbw8L83kV9awbD0JH45rptXr9e3Y8Kpnhp2u6HGrg27ylrPLdzJfe+tp6S8yuvX6p/aij9e2huAP3y8iYLjFV6/ZjDRxOAjH609wIJtR4iPDudv/zGg0YE7nrK/sIzrX/2el7/d5ZPrKVWf7YdLeOmbbD7beJDth0p9cs2bzu/MBd3bUFRWpe1t50gTgw8UnajkKWdd52OX9iE10bONzWeTc/QEK/cU8tyCH8jO880fZFPNmQPTp1sdhfK2GrvhkX9votpuuHF4Z4Z1ObexOs0lIjxzZT/iIsOYu+mwVimdA00MPvDMl9soPFHJ+V2TuHpIqk+vfUH3ZK4flkZVjeHxOVvwp3Erl18OjzxidRTK295ekcP6/cdo3zKah6b09Om1UxNjeeRiR5XSE3O2cLxCZyFuCk0MXlZVY+dQcTmRYTae+mm/Jk914UkPTe5Fq9gIlmUf5cvNh5t1jpwc6NULfv5zyMiAadNgwQIYNQq6d4dVqxyPkSNh0CDHzx07HMf+7W9w222O55s2OY4vK4MZM+Ceexzbb7kF7r4bxo2Drl3h228dx/Tu7XivVosWPz6fPfvH95p6vPKto8cr+J/5PwDw5NS+Hh/Q1hTThnViQFor8korePGbbJ9fPxBpYvCyiDAbb902jM9+PZrzkls0foAXJMZF8uBkx53aXz7fSlll8+6asrPhvvtg40bYvh3+9S9YuhSefRaeftqROL77DtatgyefhN//3nHcb37jOPbjj+HWW+H//g9i66lNKyqCRYvg73+Hyy6D+++HLVscyWT9+sbjc/d45XnPLdhJaUU1Y3sme60XUmNsNuGJy/pgEzhWVuVXpWZ/pYnBB0SEnu09P17hXFw3tBP9UhI4WFzOa0v2NOscXbpAv35gszmGHUyY4JjJol8/R4miuBiuucZRIqj9UgbH/jNmwE03wZgxjlJGfS677MfztWtX91o5OY3H5+7xyrN2HinlX6v2EWYT/uCszrHKoE6JLH5gHM9caU2pPdBoYvCSiuoaHpq9gR+O+EeDb5hN+MMljj/OV77bTeGJynM+R1TUj89tth9f22yOBeT+9CdHVc7mzfDZZ1Be/uP+O3c6qoEOHmz8/K7ndj0/1F22wfX8TT1e+c5Tc7dRYzdcNzSN7u2svTEC6NTad50+Ap0mBi95e8VePsjK5b731vtN0fX8rq0Z0yOZ4xXVvOSFutbiYkhxLqw1Y0bd7ffd56hmOnrU0TbQXO3awbZtYLc7qqaUf1qeXcDiHfm0iArn/ok9rA7nFGMMS3bm89inm/3m79IfaWLwkisGpfCzEZ15eEpPvyq61vYKeev7vRw45tlJxh56CB591FFVVOMyE8f998Mvfwk9esDrrzt6IuXlNe8a06fDpZfC+PHQIUAnkg12xhj+9rWjwfnOn3SlTYuoRo7wnbLKGu751zreWrGXJTsLrA7Hb+m02yHo3lnrmLPhINdmpvJfVw+wOhwVZJbszOem11fRKjaCJQ+Ns6Qn0tm8/f1ejpdXc/PIzsRG+moRS//g02m3RWSKiOwQkWwROaNnuoj8XUTWOx8/iMgxl/dqXN6b44l4rFRRXeP300/8blIPwmzCR2sPsL+wzOpwVJDpkBDDRRntufMn5/ldUgDHiOi7x54XcknhXLj9LyMiYcCLwEQcazivFpE5xpittfsYY+532f/XwCCXU5w0xgTwKvZ1vbE0hw+z9vP45X0Z0yPZ6nDq1bl1HNdmphIZZiMqQmsTlWd1a9uCf944JCDq8MuraogKt/lVda8/8ETKHAZkG2N2A4jIe8BUYGsD+1+PY+nPoFNWWc2rS5rX48fXnrZosJ0KHf7++/X2ihyeW7CT568fxKhubawOx6944nYxBdjv8jrXue0MItIZ6AIsctkcLSJZIvK9iFzhgXgs8/7q/RSeqGRgWit+0t2/f9H8/Y9WBZ61+4qY9tr3LM8OjEbd4pNVHD1RyUuLdTT06TyRGOr7hmmoDHkdMNsY47p6TCdnY8gNwHMicl69FxG5w5lAsvLz892L2Atq7IY3ljkGjt015ryA+OI1xvDJugNMfXEZRQFQylH+bcayHJZlH2VJgCSGm0ak0yIqnGXZR1m//1jjB4QQTySGXCDN5XUq0NAwpuuAWa4bjDEHnT93A4up2/7gut8rxphMY0xmcrL/1d3P23KY/YUn6dw6lol92lkdTpOICP9em8uG/ceYvSbX6nBUgPvz1AwemtKTW0emWx1KkyTERHDj+Z0B+KeWGurwRGJYDXQXkS4iEonjy/+M3kUi0hNIBFa4bEsUkSjn8zbAKBpum/Brry7ZDcDto7v4bK0FT/jNhd35n2sG8LORna0ORQW4hNgIfjm2G21bRlsdSpPdNjqdiDDh661HtIeeC7cTgzGmGrgHmAdsAz4wxmwRkSdF5HKXXa8H3jN1uyr0BrJEZAPwDTDdtTdToFizt5B1+47RKjbC59Nqu2tI5ySuGpJKVHiALAGq/M6JiurAWVv8NG3jo7msf0fsBt5akWN1OH7DI30VjTFzjTE9jDHnGWOecm57zBgzx2WfJ4wxj5x23HJjTD9jzADnz9c9EY+vvfKdo7Rw4/DAHjBT6oMlF1XweWPpHkb/9ZuAXQjnllHpALy3ej8ndL0GQKfEcNv+wjLmbz1CZJgtoKtj/mf+DoY/vZC1+4qsDkUFkOoaO++u3EfB8Qpa+uFgtqbon9qKIZ0TKS2v5qO12tYGmhjcNmvVPoyBi/u1p2184NStnq7abiirrOH1pc2bkluFpgXb8jhcUk7X5DhGdWttdTjNdquz1PDm8hzsfj5zgS9oYnBDRXUNH2Q5hnDU9m4IVDePSCfMJny1+TB5JeWNH6AU8M73ewFHNWogdNFuyOS+7emQEM3u/BN8t9P/usP7miYGN+zOP4Ex0Kt9PEM6J1odjlvaJ0QzsXc7auzmVLJT6mx25R9naXYB0RE2rgqwTheniwiznbq5e3flPoujsZ4mBjf07tCS5Y+O5+UbhwT03VKt64d3AmDWqv1+PxGgsl5taeGKgSkkxARm+4KrazPTCLcJu/KPU1EdmL2sPCVwu9D4iajwMNLbxFkdhkdc0K0NaUkx7C88yXc78xnXs63VISk/VVZZfWpQZKBXo9ZKjo/i83tH06NtPLYAGovkDVpiaKbvdx+lJMi6d9pswnVDHaWGf2lxWp3FnPUHKS2vZnCnVmSkJFgdjsf0at8y5JMCaGJolrLKan4xM4vhTy0MuobaazJTCbcJi7bncbg4uD6b8pz3ne1Q04YHR2nhdIeLy9mdf9zqMCyjiaEZCkoryUhJoE/HlgE1/L8p2sZHM6mvoxH6/dXaCK3OtPNIKev2HaNFVDgX9wu+9VU/33iQkdMX8tevtlsdimU0MTRDp9axzLrjfP71i+FWh+IVNwxz3AW+v3qfNkKrM3zobFu4bEAHYiKDbyqVYV2SiAoPIzoiLGTHNGjjsxuCdX6hkee1PtUIvWLXUUb7+doSyrdW5xQCcE1mWiN7Bqa28dGs/uOFtIgK3a9HLTGco4XbjrB2X1FALFvYXDabcOUgR7/0ZbsCY2595Tv/vmskH9w5gkFprawOxWtCOSmAlhjOid1ueOzTLRw4dpIP7hzBsC5JVofkNdOGd2Jy3/b06djS6lCUn7HZJKh/92tV19hZsrOAtKRYurVtYXU4PqUlhnOwYvdRDhw7SUqrGDIDfKRzY9q2jNakoOooPlkVdL3wzua5BTu5dcZqZi7PsToUn9PEcA4+dHbRu2pIakj1dT547KTVISg/8MHq/YyYvogXFu20OhSfuKS/o8fVnA0HQ24ktCaGJiopr+LLzYcBuCbA54VpKmMM0177npHTF+nqVopDxeUI0KNdvNWh+ETvDi3p3aElxSer+GZ7ntXh+JRHEoOITBGRHSKSLSKP1PP+LSKSLyLrnY+fu7x3s4jsdD5u9kQ83vDFxkNUVNs5v2sSaUmxVofjEyJCcoso4iLD2HaoxOpwlMUeu6wPq/9wIeN6hc5UKVcNTgFg9poDFkfiW24nBhEJA14ELgL6ANeLSJ96dn3fGDPQ+XjNeWwS8DgwHBgGPC4ifll5/+l6xy/GlYNDo7RQ6/cX92b1Hy9kUt/2Voei/EBiXCQRYaFT0TB1YAphNmHxjjyOHq+wOhyf8cT/8DAg2xiz2xhTCbwHTG3isZOBr40xhcaYIuBrYIoHYvKoQ8UnWbmnkMhwG1MyQusLsm3L6IBerlS5z243LM8uCMnBjsnxUYzpkUy13TBnw0Grw/EZTySGFMB17oRc57bTXSUiG0VktojUjoxp6rGW+mzDQYyBCb3aBuzyhe4qr6ph84Fiq8NQFli5p5AbXlvJ1S8vtzoUS1zprE76aG3oVCd5IjHU1z3n9FuLz4B0Y0x/YAEw8xyOdewocoeIZIlIVn6+b1dY+nS9405h6kC/y1k+cbi4nMy/LOCm11dSVWO3OhzlY7XVqCO6Bu7Sne64sHc74qPC2XSgOGQm1vNEYsgFXMfGpwJ1ylzGmKPGmNoKuleBIU091uUcrxhjMo0xmcnJyR4Iu2my80rZcrCE+Ohwxvb03XX9SbuWUbRPiKaorIql2ToSOpRUVNcwd9MhAK4YFJo3RtERYafa2D7feMjiaHzDE4lhNdBdRLqISCRwHTDHdQcRcZ2C8XJgm/P5PGCSiCQ6G50nObf5jTnO0sJFGe2JjgjOuZEaIyJcPqAjAJ+tD516VgWLd+RTUl5N7w4tQ6aban0uG/DjmIZgng6nltuJwRhTDdyD4wt9G/CBMWaLiDwpIpc7d7tXRLaIyAbgXuAW57GFwJ9xJJfVwJPObX4jPMxGq9iIkK1GqlWbGOZtOUx5VWgN9glltdVIVwzsaHEk1hrVrQ2JsRFk5x1n++FSq8PxOo90NzHGzAXmnrbtMZfnjwKPNnDsG8AbnojDG+6d0J27xpxHeAiNdK5Peps4+qcmsDG3mEXb84JyHn5VV0l5FQu25SECl4d4YogIs3Fxvw4s3pHPkZJyencI7uliQqdDshsiw20hNQVGQ2pLDXO0OikkzNt8mMpqO8O7JNEhIcbqcCz3+4t7s/ThcYwNgbXQNTE0oMZu+GTdAUqDbF1nd1zavyMisGhHXtCtd63OVNvQevmA0K5GrRUXFY5IaNwgamJowMo9R/nN++u55uUVVofiN9onRDMsPYnKajvztxyxOhzlRcfKKlmWXUCYTUJuUGdj8krLWbn7qNVheJUmhgbYRBjeJYmJfdpZHYpfqa1rDqVRoKFo/pYjVNsNI89rTVJcpNXh+I3svOOc//RC7pm1LqhHgmtiaMD5XVvz/p0j+O3EHlaH4lcuzuhAuE1Yll1A4YlKq8NRXvKFc+yCdjKo67zkOM5LbsHAtFYcKwve339NDI0IlTrFpkqMi2RktzbU2A1fbz1sdTjKCyqr7WTnHSfMJkzWyRPrEBG+vO8CXv1ZJq1bRFkdjtdoYqjHV5sPsy7I13V2xyX9HF8Wa/YWWRyJ8obIcBtLHhrH578erdVI9QgPgdllddrM09TYDX/8ZDMFxyv44t7R9O2YYHVIfueifh0YkNaKniE8EjbY2WwS9H313VFVY2fl7kLaJ0TRrW3w/R0Ef+o7R6tzCik4XkGnpFj66B9GvVpGR9CrfUutZgtCZZXVFGnbUaP+d+FObnx9JW+t2Gt1KF6hieE0c10a3fSLr3H6JRJcPt9wiMynFvBfX223OhS/NrGPozr1y82HsQdh7yRNDC5q7ObUus4X99NGt7OpqrFz5UvLGP7MQh3sFkRyi8oQIDUxNJavba6MlJakJsaQX1rBmn3B19amicFFVk4h+aUVpCbG0C9F2xbOJiLMRlR4GGEibD2o60EHi99O6knWHy9kaojPjdQYETnVlbe2liGYaGJwUfsffIlWIzXJX6/qz5o/Xcj5IbqAS7BqFRtJXJT2S2nMRc4R4V8FYXWSJgYne51qJB3U0xSdWsfqetBBZPvhkqAezetpA1Jb0SEhmkPF5WzIPWZ1OB6licFpzb4i8korSGkVQ/9UrUY6FxXVNeSVlFsdhnJDcVkVlz6/lNF/XaTrbTSRzWUeqdqbymChicHpi421vZHaazXSOfj2h3wy/7yAxz7dYnUoyg2LdjjmRkpvHReyKxU2h2s7QzANiPVIYhCRKSKyQ0SyReSRet7/rYhsFZGNIrJQRDq7vFcjIuudjzmnH+sLxhjmb3Fk/Iu0Gumc9GwXT2lFNd/syONERbXV4ahmqp0td3JfnTTyXAzplEjb+Chyi06y+UDwdMJwOzGISBjwInAR0Ae4XkT6nLbbOiDTGNMfmA38l8t7J40xA52Py7HA5gMlHCwup218FANTW1kRQsBqnxDNkM6JVFTbWbwj3+pwVDOUV9Xw7Q+O/7uJOjfSOalbnRQ8vZM8UWIYBmQbY3YbYyqB94CprjsYY74xxpQ5X34PpHrguh6zv6iMhJgIJvZppyu1NUPtXeZ8nVQvIC3LLqCssoZ+KQmktNKV2s7VRRmOWoYvNx8OmuokTySGFGC/y+tc57aG3A586fI6WkSyROR7EbmioYNE5A7nfln5+Z69M724Xwey/nghD03u5dHzhopJzlGgi7bnUVlttzgada7mOatRJ+naI80yND2RxNgIyiqrORokMwF4oq9hfbfY9aZNEbkRyATGuGzuZIw5KCJdgUUisskYs+uMExrzCvAKQGZmpsfTckSYjYRYbYtvjvQ2cfRsF8+OI6V8v/soP+mRbHVIqolq7IYF2/IAmKTVSM0SHmZjzj2jSWkVEzQ1Dp74JswF0lxepwJnLO8lIhcCfwAuN8ZU1G43xhx0/twNLAYGeSCmJttTcEIbTT2gtjqp9u5TBYY1e4soPFFJ59ax9GjXwupwAlZaUmzQJAXwTGJYDXQXkS4iEglcB9TpXSQig4D/w5EU8ly2J4pIlPN5G2AUsNUDMTXZAx9uYNCfv2bVnkJfXjbo1N5tfr31SNCNAg1m812qkbSbtvuOHq8IirnD3E4Mxphq4B5gHrAN+MAYs0VEnhSR2l5G/w20AD48rVtqbyBLRDYA3wDTjTE+SwyV1XZsAjaBvh11im139O3YkpRWMeSVVrA+yEaBBitjDPO3OrqpajWS+/5n/g6GPrWAj9cesDoUt3lkPgNjzFxg7mnbHnN5fmEDxy0H+nkihuaIDLfx4V0jKSmv0rlh3CQiTOrbjjeX5TBvy2EGd0q0OiTViB1HStlXWEbruEj9//KALm3iCLMJR4JgFgBtbcWx8IxyX23vpPlbjgRNt71gttDZ6DyxTzvCgqh+3CoXZXRgzZ8m8tCUwO/dGLK3yScqqtlTcIK+HXUlMk+p7ba3p+AEu/KPB+WSh8Hkzp90ZUjnRBJjdV1nT4iJDCOG4JhOJGQTw8Ltedw7ax2X9OvAi9MGWx1OUAgPs/HMlf1JTYzhvGTt4eLvwsNsOmW6F9TYDbvzj9M9gNdED9nEUNutcnBnrVv1pNrpAZR/s9tNUHWv9Bel5VWM/e/FnKisZt2fJhETGZgliJBsY6iormHxduegHh3t6TXazuC/bn5zFT97YxU5BSesDiWoxEdHkJIYQ3mVnSU7A3fusJBMDMuzj3KisoY+HVqSlqRr23ragq1HuPqfy3nn+71Wh6LqcbyimpW7C1meXUBinLYveFrtzWZtV+BAFJKJoXayt0k6xbBXlFZUkbW3KKD/MIJZi6hwVjw6nldvziQhRnvkedpk55iQhduOUF0TmHOHhVxiqLEbvt5aO/e81od7w/he7XjxhsH888YhVoeiGtC6RRTjera1Ooyg1K1tC7q0iaOorIrVOUVWh9MsIZcY1u0rouB4JWlJMfRqH7i9BvxZQkwEl/TvQAsdNOh3auxG2368rHawJwTuVPQhlxhqeyNN7qNLePqCfgn5lwXbjjDimUW8tmS31aEEtUAf7BlSicEYw7zaJQy1W6VX1dgNv/1gPSOeWURZpc5e6y/mbznC4ZJyKnTdDK8alNaK5PgoDhw7yZaDgbfkZ0glBp0bxnfCbMKu/BMcLilnyc4Cq8NRQHWNnYXbdW1nX7DZhIkB3DsppBLDvM2O/yCdG8Y3TnXb2xJ4fxjBaHVOEcfKqujaJk5HpvvAj7//gdfOEFKJYWm2Y8CJdlP1jVPd9rYHbre9YFLbEDqxr6694Asjz2tDfFQ42w+XsvdoYA0kDKnE8M7Ph/PmrUMZeV4bq0MJCd3atqBrchzHyqpYlaMLIVnJGHOq5KbdtH0jMtzG2F6OLsGLtuc1srd/8UhiEJEpIrJDRLJF5JF63o8Skfed768UkXSX9x51bt8hIpM9EU9DosLDGNezLdERgTl/SSBy7Z2hrLP1UAkHjp0kOT6KgamtrA4nZNz5k658eNcIfjYi3epQzonbiUFEwoAXgYuAPsD1ItLntN1uB4qMMd2AvwN/dR7bB8dSoH2BKcBLzvOpIFFbbff11sDsthcsanvjTezTTifP86GMlASGpicFXJumJ0oMw4BsY8xuY0wl8B4w9bR9pgIznc9nAxPEUck5FXjPGFNhjNkDZDvPp4LEwNRWtA3gbnvBwnVtZ2WNQLox8kRiSAH2u7zOdW6rdx/nGtHFQOsmHqsCWKB32wsG+46Wsf1wKfFR4dq+ZoGdR0q56fWV3P3OWqtDaTJPJIb6ykinp8aG9mnKsY4TiNwhIlkikpWfH7jT2Yai2oXmA7HbXjCo7Y00tldbIsNDqr+JX0iIjWBpdgHf7cynvKrG6nCaxBO/JblAmsvrVOBgQ/uISDiQABQ28VgAjDGvGGMyjTGZycnJHghb+cqIrq0DttteMKgtqWk1kjXaxkfz2s8yWfbw+IDp+OKJxLAa6C4iXUQkEkdj8pzT9pkD3Ox8fjWwyDgq3OYA1zl7LXUIS8CDAAAdkElEQVQBugOrPBCT8iOR4TbGObvtfa3VST5334Tu3HR+Z8b21Bsqq0zo3S6g1r5we/pLY0y1iNwDzAPCgDeMMVtE5EkgyxgzB3gdeFtEsnGUFK5zHrtFRD4AtgLVwK+MMYFR1lLn5KohqaQkxjC6u9Zx+9qobm0Y1U3/3f2B3e6oKff3nmESSC3ltTIzM01WVpbVYSilVJO9+E02M5bn8PdrB1p2gyQia4wxmY3tpy1RSgWpsspq7nw7iw+z9je+s/K6k5U15JdWBMQaDZoYlM8Un6zizWV7eHbeDqtDCQnf/ZDPvC1HmLVqn9WhKH4c7BkIazToElvKZyqqa3jy861EhNm4e+x5xOkKb16VmZ7EUz/NIDE2cBo9g1m/lATat4zmcEk5mw4U09+PpybRv0zlM23jo/nl2PPo3jY+4KYICERtWkQxbXhnq8NQTrVLfr61Yi/zthz268SgVUnKpx6c3IsrBqUETH9upTwpUCaV1MSgVBD634U7efKzrTqg0M8M75pEy+hwduYdZ3f+cavDaZAmBuVzq/YU8vDsjazao2s0eIPdbnh35T7eWLaH4pNVVoejXESE2ZjQ+8cZh/2VJgblc9/9kM/7Wfv5fGO9s58oN208UMzhknI6JETTLyXB6nDUaSYFwKSSmhiUzwVSt71A5DrFti7h6X9+0iOZyHAba/cVkVdabnU49dLEoHyuX0oCHRIc3fY25hZbHU7QmedMDLqEp3+Kiwrngm5tMAYWbPXPJT81MSifExGX4rT/jwINJNl5x9mVf4KEmAiGdkmyOhzVgFOlZj/9/dfEoCzx4xoN/lvPGohqv2gm9G5LRJj+efurCb3bccvIdO4ac57VodRLB7gpSwzrUrfbXtfkFlaHFBRqE21tf3nln9q0iOKJy/taHUaD9JZCWcK1254/984IJIeLy1m//xjRETbG9NC1F1TzaWJQlpl8qneSf9azBpqvtzkS7AXdk4mJ1JHl/s4Yw3ur9nH3O2uoqPavZWg0MSjL/KRHMlHhNtbtP0ZeiX922wsk87U3UkAREWYsz+HLzYf5frd/DfZ0KzGISJKIfC0iO50/E+vZZ6CIrBCRLSKyUUT+w+W9GSKyR0TWOx8D3YlHBZbYyHAu6O7strfNP7vtBYrik1Ws2HWUMJswwbmMqvJ/d489j+lX9qO/nw1EdLfE8Aiw0BjTHVjofH26MuBnxpi+wBTgORFxnVbwQWPMQOdjvZvxqABT20g6T6uT3HKysoarh6QyJaN9QK0tHOqmDkzhumGd/O7/zN1eSVOBsc7nM4HFwMOuOxhjfnB5flBE8oBk4Jib11ZBYELvtnRpE0efji2tDiWgtU+IZvpV/a0OQwUJdxNDO2PMIQBjzCEROWsZVkSGAZHALpfNT4nIYzhLHMaYCjdjUgGkdYsovnlgrNVhKGWZ7LzjvPP9XlJaxfCLn3S1OhygCVVJIrJARDbX85h6LhcSkQ7A28Ctxhi7c/OjQC9gKJDEaaWN046/Q0SyRCQrPz//XC6tVFDbsP8YH6/L1ZlUA1ReaTkzlucwa7X/LMHaaGIwxlxojMmo5/EpcMT5hV/7xV9vC6KItAS+AP5ojPne5dyHjEMF8CYw7CxxvGKMyTTGZCYnax/tYHOkpJx3V+71u257geCtFXu5//0NvLU8x+pQVDMMS0+iVWwEu/NPkJ3nH2s0uNv4PAe42fn8ZuDT03cQkUjgY+AtY8yHp71Xm1QEuALY7GY8KkDd+uZq/vDxZr/rthcIzu+axPldk7ioXwerQ1HNEB5mY0Iv/5o7yd3EMB2YKCI7gYnO14hIpoi85tznWuAnwC31dEt9V0Q2AZuANsBf3IxHBahLB3Tgwt7taBGlA7PO1TWZabx3xwi6tdVpRQJV7aR68/xk7jAJxPnwMzMzTVZWltVhKKWUR5ysrGHwn7/mZFUNyx4ZT0qrGK9cR0TWGGMyG9tPRz4rFaCqa+z897ztrNtXpAseBbiYyDDGOwcmfrnpkMXRaGJQfqS6xs6Snfl8uv6A1aEEhJV7Cnnxm1088OEGq0NRHnCxs43o842aGJQ6ZeuhEm56fRV/+WIbNXa9A27MXOed5cX9OugSnkFgXK9koiNsrN9/jAPHTloaiyYG5Tf6pSSQmhhDfmkFWTnaO+lsauzm1DQiF2Vob6RgEBsZ7jfVSZoYlN8QES5xFqfn+kE9qz9bnVNIwfFK0lvH0rtDvNXhKA+prU76QhODUj+6pL/jD+PLzYexa3VSg2rvKC/SaqSgMr5XW6IjbKzbd4yDFlYn6dKeyq/UViflFp0ka28Rw3RB+zPY7YYvNzuqkS7WaqSgEhsZztVDUjEG7Bb2NNMSg/IrWp3UuLX7isgrrSA1MYaMFJ2VNtj85Yp+PPXTfqQmxloWgyYG5XcudkkMWp10prmbnKUFrUZSXqKJQfmd/qmO6qS80gqy9hZZHY5fqbEbvth0EICLMnQJz2BVfLKKD7P28/VWa6bI0MSg/I6I1Ck1qB+t2lPIkZIK0pJiGJjWqvEDVED67od8Hpy9kZe/3dX4zl6giUH5pdp2hi83a3WSqzkbHKWFy/p31GqkIDa+V1vG9EjmqsGplkx3oolB+aXa6qQjJRWs9vBgtzlzYPr0s+9z8CBcfbVHL+sRLaPDaRkdzmUDOlodivKiuKhwZt42jBuGd7LkBkBnV1V+a/qX2/l0/QEev6wPU7Rb5imV1XYiwkRLDOqc6eyqKuDdO6Ebyx4ef05JIScHevWCn/8cMjJg2jRYsABGjYLu3WHVKpgxA+65x7H/LbfAvffCyJHQtSvMnv3jeTIyHM9nzIArroDLLoMuXeCFF+Bvf4NBg+D886HQWaAZOxZq71cKCiA9/dyOb6rIcJsmhRCxMfcYT8zZwp6CEz69riYG5bdiI8Ox2c79CzA7G+67DzZuhO3b4V//gqVL4dln4emnz9z/0CHH+59/Do88Uv85N292nGfVKvjDHyA2FtatgxEj4K23Go/J3ePLq2r4dP0BTlRUN76zChozl+9lxvIcPlnn2xmH3UoMIpIkIl+LyE7nz8QG9qtxWb1tjsv2LiKy0nn8+85lQJWqo+B4BYt31LuceL26dIF+/cBmg759YcIEEHFsy8k5c/8rrnDs26cPHGmgd+C4cRAfD8nJkJDguPuHhs/p6eMXbc/jvvfWc8ubqxrfWQWNKwY52pI+XX/Ap43Q7pYYHgEWGmO6Awudr+tz0hgz0Pm43GX7X4G/O48vAm53Mx4VZApPVDLimYXc9c4ajjfxbjkq6sfnNtuPr202qK7nFK77N/S315RzhoeD3e54Xl7uXkyni40MI7NzIpP76tiFUDKia2vatIgi52gZG3OLfXZddxPDVGCm8/lM4IqmHiiOStLxwOzmHK9CQ1JcJEPTkxh1XhuKTlRaHc5ZpafDmjWO57VtFZ4ytmdbZt89kttHd/HsiZVfCw+zcdkARxvbJz5cwMrdxNDOGHMIwPmzbQP7RYtIloh8LyK1X/6tgWPGmNr7pVwgpaELicgdznNk5efnuxm2CiRv3z6c128ZSlqSdXPHNMUDD8A//+loyC4o8M41tNE59Ewd6Pha/GzDIapr7D65ZqPdVUVkAVBf+fUPwExjTCuXfYuMMWe0M4hIR2PMQRHpCiwCJgAlwApjTDfnPmnAXGNMv8aC1u6qKpTMXJ7DkM6J9O3YUhNDCDLGMO7ZxeQcLePt24dxQffkZp/LY91VjTEXGmMy6nl8ChwRkQ7OC3YA6m0hNMYcdP7cDSwGBgEFQCsRqZ36OxU42ITPpkJQjd2wPLuAZdleuhX3U7lFZTw+ZwtX/XN5k9tYVHARkVOlhk/W+eYr0t2qpDnAzc7nNwOfnr6DiCSKSJTzeRtgFLDVOIoq3wBXn+14pQC+2nyYG15byX/N22F1KD718VpHvfKkvu2Jj46wOBpllakDHb2T5m05THlVjdev525imA5MFJGdwETna0QkU0Rec+7TG8gSkQ04EsF0Y8xW53sPA78VkWwcbQ6vuxmPClLje7WlRVQ4G/YfIzuv1OpwfMIYw0fO/utXDW6w+U2FgK7JLRiQmkBaUqxPVnZzawU3Y8xRHO0Fp2/PAn7ufL4cqLfdwFm1NMydGFRoiIkM49L+HXhv9X4+zMrl0Yt7Wx2S163dV8SeghO0jY9yq15ZBYe3bh9OQoxvSo068lkFjGsyUwH4aN0Bn/XOAGD/frjoIt9dz2n2Gkdp4aeDUghrxghwFVx8lRRAE4MKIIM7JdI1OY780gq+/cGHXZaLix3JwYfKq2r4fKOjofHKwak+vbZSmhhUwBARrhmSBsAHWb79om5wSLSXLNh2hNLyajJSWtKzfbxPr62UJgYVUK4cnIJNYOG2PI4er/DNRS0YOzB7TS4AV2lpQVlAE4MKKO1aRjOmRzLVdsMn63047MWHJYbcojK+/SGfyDDbqf7rSvmSJgYVcK7NdFQnfZi13zczTor4NDF8sHo/xsCUjPYkxemEw8r3NDGogDOhdzsSYyPYfriUTQd8MOOkD6uSqmvsvO9sP7lheCefXVcpV5oYVMCJDLedqnt/5/u9vrmoj0oMJypqGN+rHf1SEhjeJckn11TqdG4NcFPKKtPO78ynGw7SyRczrvqwxJAQG8EzV/bDGKMT5inLaGJQAalLmzhWPDKe8DAfFXp93F1Vk4KykiYGFbB8lhR89CU9e00u4TZhSkZ7oiPCfHJNpeqjbQwqoBWfrOKNpXtYs7fQuxfycomhorqGv361nd+8v551+4559VpKNUYTgwpob6/I4cnPt/LKd7u9dxEflBgE4XcTe3BJvw6c31UbnZW1tCpJBbRrh6axKqfI+yOEvVxiiAy3cd2wTlw3TLuoKutpYlABrW18NG/d5uWZ2308wE0pq2liUKoxXq5Kemj2BuKjI7hrzHkkx0d59VpKNYVbbQwikiQiX4vITufPxHr2GSci610e5SJyhfO9GSKyx+W9ge7Eo0LXziOl3PfeOmYs2+OdC3ipxJBbVMbsNbnMXJ6DXUslyk+42/j8CLDQGNMdWOh8XYcx5htjzEBjzEBgPFAGzHfZ5cHa940x692MR4WovUfL+HT9QV5dsocqTy/i48USw4xlOdgNXNK/A+1aRnvtOkqdC3cTw1RgpvP5TOCKRva/GvjSGFPm5nWVqmN8r7Z0TY7jwLGTzN10yPMX8MLdfNGJSt5duQ+AX1zQ1ePnV6q53E0M7YwxhwCcP9s2sv91wKzTtj0lIhtF5O8i0mAFq4jcISJZIpKVn+/D1btUQLDZ5NSX6yvf7fbsrKteKjG8uTyHk1U1jO2ZTEZKgleuoVRzNJoYRGSBiGyu5zH1XC4kIh2AfsA8l82PAr2AoUAS8HBDxxtjXjHGZBpjMpOTdWF0daafDkqhTYsothwsYfEOD988eLjEcLyi+lR7yK/GdfPouZVyV6OJwRhzoTEmo57Hp8AR5xd+7Rd/3llOdS3wsTGmyuXch4xDBfAm4OV+hyqYRUeEcdcYR6nhuQU/eK7U4IUSw7vf76WkvJph6UkMTdcBbcq/uFuVNAe42fn8ZuDTs+x7PadVI7kkFcHRPrHZzXhUiJs2vDNtWkSyIbfYs6UGD5YYyiqreXWJo7Twy3Hneey8SnmKu4lhOjBRRHYCE52vEZFMEXmtdicRSQfSgG9PO/5dEdkEbALaAH9xMx4V4mIiw7hrjOPL1mOlBg+XGGYsz6HgeAUDUhMY00OrRZX/cWuAmzHmKDChnu1ZwM9dXucAZyxea4wZ7871larPtOGdefnbXWzILWbR9jwm9G7n/kk9VGIoLqvi5cW7AHhoSi+dXlv5JZ1ETwUd11LD9C+3U+3uuAYPTonx8ne7KCmvZlS31ozq1sYj51TK0zQxqKB004jOpCXFsDPv+Kk1lJvNQ3f1xhi2HyoB4MHJvTxyTqW8QRODCkpR4WE8PKUXIpBTcML9E3qgxCAivHHLUD7/9WgGprVyPyalvEQn0VNB65J+HejZLp7u7eLdO5HNBnbPTLMhIjqYTfk9LTGooCUi7icFgLAwtxJDjd3w2Keb2XG41P1YlPIBTQwqJCzLLuDBDzc0r/uqzQY1Nc2+9r/X5vLWir3cPnO1+w3hSvlA0FQlVVVVkZubS3l5udWhBJXo6GhSU1OJiIiwOpRmK6us5t5Z6zh6opIxPZO5tH/HczuBmyWGizLas25fEaO6tSE8TO/FlP8LmsSQm5tLfHw86enp2jfcQ4wxHD16lNzcXLp06WJ1OM0WGxnO45f3ZX9hGZP6tD/3E7hZYoiPjuCZK/s3+3ilfC1oEkN5ebkmBQ8TEVq3bk0wzGZ7+YBzLCW4amaJYXVOIRkdE4iJDGv+tZWyQFCVazUpeF4w/pvmlZbzxcZzWLOhGSWGLQeLmfbaSi5+fglFJyrPMUKlrBVUicFfjR07lqysrLPu8/TTTzf43ocffkjv3r0ZN24cWVlZ3HvvvZ4OMWQUl1Vx8T+WcN9761i+q6BpB51jiaGkvIpfvruWymo7w7skkRgX2cxolbKGJgY/cbbE8Prrr/PSSy/xzTffkJmZyfPPP++Ra1ZXV3vkPIEkITaCq4ekUW033P3OWvacbfBbTQ3ceCNccgmUl0NmJtx661nPX1Vj51fvrmXv0TL6dGjJE5f39fAnUMr7NDF4SE5ODr169eLmm2+mf//+XH311ZSVnbmC6axZs+jXrx8ZGRk8/LBjXaJHHnmEkydPMnDgQKZNm1Zn/yeffJKlS5dy11138eCDD7J48WIuvfRSAPLz85k4cSKDBw/mzjvvpHPnzhQUFJCTk0NGRsapczz77LM88cQTgKP08vvf/54xY8bwj3/8g/z8fK666iqGDh3K0KFDWbZsmZf+hfzHg5N7cmHvthSfrOK2GavJK2mgJ5vNBitXwuLFjpHP69ZBVVX9++JorH/43xtZsrOANi0iefnGIURHaPuCCjxB0/h8uvRHvjin/TNSWvL5ry844/ic6Zc0+Rw7duzg9ddfZ9SoUdx222289NJLPPDAA6feP3jwIA8//DBr1qwhMTGRSZMm8cknnzB9+nReeOEF1q9ff8Y5H3vsMRYtWsSzzz5LZmYmixcvPvXef/7nfzJ+/HgeffRRvvrqK1555ZUmxXns2DG+/dYxA/oNN9zA/fffz+jRo9m3bx+TJ09m27ZtTf7MgSjMJjx33SCufXkFWw+VcMNrK5n1i/NJjj9tZVkR+N//hauvhhMnIDISHnus3nPW2A1//GQTH609QExEGG/cMpROrWN98GmU8jwtMXhQWloao0aNAuDGG29k6dKldd5fvXo1Y8eOJTk5mfDwcKZNm8Z3333X7OstXbqU6667DoApU6aQmJjYpOP+4z/+49TzBQsWcM899zBw4EAuv/xySkpKKC0N/hG6LaLCeefnw+nVPp7svONc8/JysvOOn7nj5MnQyznh3Zgx0KPHGbuUV9Vw//vrmbVqP1HhNl6+aQj9U3UuJBW43CoxiMg1wBNAb2CYcx2G+vabAvwDCANeM8bULujTBXgPx3rPa4GbjDEe6cJxLnf6njr+9B48p7/26AL1ZzlfeHg4dpfG0tMH/cXFxZ16brfbWbFiBTExMR6NLRAkxUXyzs+H87PXV7H1UAk/fWkZ/331AKZkuIx1EIEXXoARI8BZHedq39EyfvWvtWw6UExcZBiv3TyUEee19t2HUMoL3C0xbAauBBq87RWRMOBF4CKgD3C9iPRxvv1X4O/GmO5AEXC7m/FYat++faxYsQJwtCWMHj26zvvDhw/n22+/paCggJqaGmbNmsWYMWMAiIiIoOos9df1GT16NB988AEA8+fPp6ioCIB27dqRl5fH0aNHqaio4PPPP2/wHJMmTeKFF1449bq+6qxg1qZFFLPvHsHkvu0oLa/mrnfW8Kt3T2uUPv98+Oorx0+niuoaXvwmm0nPfcumA8WkJcXw/p0jNCmooOBWYjDGbDPG7Ghkt2FAtjFmt7M08B4w1bnO83hgtnO/mTjWfQ5YvXv3ZubMmfTv35/CwkLuvvvuOu936NCBZ555hnHjxjFgwAAGDx7M1KlTAbjjjjvo37//GY3PZ/P4448zf/58Bg8ezJdffkmHDh2Ij48nIiKCxx57jOHDh3PppZfSq1fDc/8///zzZGVl0b9/f/r06cPLL7/cvA8fwGIjw/nntCE8flkfYiLC+GLTISb8z2JW7Dp6ap/8kWPZlX+cKudcRzYR/rVyH+VVdi4f0JHP7hmts6aq4GGMcfsBLAYyG3jvahzVR7WvbwJewLHGc7bL9jRgc1OuN2TIEHO6rVu3nrHNl/bs2WP69u3r02uWl5ebqqoqY4wxy5cvNwMGDPDKdaz+t/WlfUdPmIc+3GAyHvvKHC+vOrX9iheXms4Pf252HC45tW3uxoNmyQ/5VoSpVLMAWaYJ37GNtjGIyAKgvglm/mCM+bQJuae+obPmLNsbiuMO4A6ATp06NeGywW/fvn1ce+212O12IiMjefXVV60OKeClJcXy16v789hlfYiL+vHPIzE2krSkGEpO/ljdd1G/DlaEqJTXNZoYjDEXunmNXBylgVqpwEGgAGglIuHGmGqX7Q3F8QrwCkBmZqZnW3E9ID09nc2bN/v0mt27d2fdunU+vWaocE0KAG/cMtSiSJTyPV90V10NdBeRLiISCVwHzHEWa77BUdUEcDPQlBKIUkopL3IrMYjIT0UkFxgBfCEi85zbO4rIXABnaeAeYB6wDfjAGLPFeYqHgd+KSDbQGnjdnXiMh7uDKv03VSoUuTWOwRjzMfBxPdsPAhe7vJ4LzK1nv904ei25LTo6mqNHj9K6deugnBHUCsa5HkN0dLTVoSilfChopsRITU0lNzc3KNYO8Ce1K7gppUJH0CSGiIiIgF5lTCml/IXOlaSUUqoOTQxKKaXq0MSglFKqDgnE7ogikg/sbcahbXAMrAsl+plDg37m0ODuZ+5sjElubKeATAzNJSJZxphMq+PwJf3MoUE/c2jw1WfWqiSllFJ1aGJQSilVR6glhqYtihxc9DOHBv3MocEnnzmk2hiUUko1LtRKDEoppRoREolBRKaIyA4RyRaRR6yOx9tEJE1EvhGRbSKyRUTuszomXxGRMBFZJyINL3QdZESklYjMFpHtzv/zEVbH5G0icr/zd3uziMwSkaCb6VFE3hCRPBHZ7LItSUS+FpGdzp+J3rh20CcGEQkDXgQuAvoA14tIH2uj8rpq4HfGmN7A+cCvQuAz17oPx/TuoeQfwFfGmF7AAIL884tICnAvjuWEM4AwHOu8BJsZwJTTtj0CLDTGdAcWOl97XNAnBhzTemcbY3YbYyqB94CpFsfkVcaYQ8aYtc7npTi+KFKsjcr7RCQVuAR4zepYfEVEWgI/wbmWiTGm0hhzzNqofCIciBGRcCCWs6z+GKiMMd8BhadtngrMdD6fCVzhjWuHQmJIAfa7vM4lBL4ka4lIOjAIWGltJD7xHPAQYLc6EB/qCuQDbzqr0F4TkTirg/ImY8wB4FlgH3AIKDbGzLc2Kp9pZ4w5BI4bQKCtNy4SComhvlV7QqIrloi0AP4N/MYYU2J1PN4kIpcCecaYNVbH4mPhwGDgn8aYQcAJvFS94C+c9epTgS5ARyBORG60NqrgEgqJIRdIc3mdShAWO08nIhE4ksK7xpiPrI7HB0YBl4tIDo7qwvEi8o61IflELpBrjKktEc7GkSiC2YXAHmNMvjGmCvgIGGlxTL5yREQ6ADh/5nnjIqGQGFYD3UWki4hE4mikmmNxTF4ljrVNXwe2GWP+ZnU8vmCMedQYk2qMScfxf7zIGBP0d5HGmMPAfhHp6dw0AdhqYUi+sA84X0Rinb/rEwjyBncXc4Cbnc9vBj71xkWCZgW3hhhjqkXkHmAejt4LbxhjtlgclreNAm4CNonIeue23zvX3lbB59fAu84bn93ArRbH41XGmJUiMhtYi6MH3jqCcBS0iMwCxgJtRCQXeByYDnwgIrfjSJDXeOXaOvJZKaWUq1CoSlJKKXUONDEopZSqQxODUkqpOjQxKKWUqkMTg1JKqTo0MSillKpDE4NSSqk6NDEopZSq4/8B0rfKxB2u9EEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "'\\nClass\\tName\\tAttrs\\nAngle angle angleA=90,angleB=0,rad=0.0\\nAngle3 angle3 angleA=90,angleB=0\\nArc arc angleA=0,angleB=0,armA=None,armB=None,rad=0.0\\nArc3 arc3 rad=0.0\\nBar bar\\n'"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = np.linspace(0.05, 10, 1000)\n",
    "y = np.sin(x)\n",
    "plt.plot(x, y, \n",
    "\tls='-.', # 折线图的线条风格\n",
    " \tlw=2,   # 折线图的线宽\n",
    " \tlabel='plot figure')\n",
    "plt.legend()\n",
    "\n",
    "plt.annotate(s='maximum', # 注释文本\n",
    "\t\t\txy=(np.pi/2, 1.0), # 被注释图像内容的位置坐标 （箭头指向的地方，即需要标注的坐标点）\n",
    "\t\t\txytext=((np.pi/2)+1.0, 0.8), # 注释文本的位置坐标（箭头开始指的地方，即放置注释文本的地方）\n",
    "\t\t\tcolor='b',\t# 注释文本的颜色\n",
    "\t\t\tarrowprops=dict(arrowstyle='-|>', connectionstyle='angle',color='r')) # 箭头的属性字典\n",
    "\n",
    "plt.annotate(s='minimum', # 注释文本\n",
    "\t\t\txy=(np.pi*1.5, -1.0), # 被注释图像内容的位置坐标 （箭头指向的地方，即需要标注的坐标点）\n",
    "\t\t\txytext=(np.pi*1.25, -0.5), # 注释文本的位置坐标（箭头开始指的地方，即放置注释文本的地方）\n",
    "\t\t\tcolor='b',\t# 注释文本的颜色\n",
    "\t\t\tarrowprops=dict(arrowstyle='-|>', connectionstyle='angle3',color='r')) # 箭头的属性字典\n",
    "plt.show()\n",
    "\n",
    "\n",
    "\n",
    "'''\n",
    "Class\tName\tAttrs\n",
    "Angle angle angleA=90,angleB=0,rad=0.0\n",
    "Angle3 angle3 angleA=90,angleB=0\n",
    "Arc arc angleA=0,angleB=0,armA=None,armB=None,rad=0.0\n",
    "Arc3 arc3 rad=0.0\n",
    "Bar bar\n",
    "'''"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## text 无指向性文本注释\n",
    "Signature: plt.text(x, y, s, fontdict=None, withdash=False, **kwargs)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y, \n",
    "\tls='-.', # 折线图的线条风格\n",
    " \tlw=2,   # 折线图的线宽\n",
    " \tlabel='plot figure')\n",
    "plt.legend()\n",
    "plt.text(x=np.pi+0.5, y=0.0, s='y=sin(x)', weight='bold', color='b',fontsize=12)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "## title 标题"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y, \n",
    "\tls='-.', # 折线图的线条风格\n",
    " \tlw=2,   # 折线图的线宽\n",
    " \tlabel='plot figure')\n",
    "plt.legend()\n",
    "plt.title('y=sin(x)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 示例"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "x = np.linspace(0.5, 3.5, 100) # Returns num evenly spaced samples, calculated over the interval [start, stop].\n",
    "y = np.sin(x)\n",
    "\n",
    "y1 = np.random.randn(100) # Return a sample (or samples) from the \"standard normal\" distribution.\n",
    "\n",
    "plt.plot(x, y, \n",
    "\tls='-.', # 折线图的线条风格\n",
    " \tlw=2,   # 折线图的线宽\n",
    " \tlabel='plot figure')\n",
    "\n",
    "'''\n",
    "matplotlib.iines.Line2D.set_linestyle\n",
    "\n",
    "linestyle\t\tdescription\n",
    "'-'or 'solid' \tsolid line\n",
    "'--'or'dashed'\tdashed line\n",
    "'-.'or'dash_dot'\tdash-dotted line\n",
    "':'or'dotted'\tdotted line\n",
    "'None'\t\tdraw nothing\n",
    "' '\t\t\tdraw nothing\n",
    "''\t\t\tdraw nothing\n",
    "'''\n",
    "\n",
    "plt.scatter(x, y1, label='scatter figure', marker=\"*\")\n",
    "\n",
    "\n",
    "#################################################\n",
    "# clean up (removing chart junk)\n",
    "# turn off the top spine and the right spine\n",
    "# 关闭上面和右边的坐标轴\n",
    "for spine in plt.gca().spines.keys():\n",
    "\tif spine == 'top' or spine == 'right':\n",
    "\t\tplt.gca().spines[spine].set_color('none')\n",
    "\n",
    "\n",
    "\n",
    "# 下面这两句可以不写，默认就打开了\n",
    "# turn on the bottom tick for x-axis \n",
    "plt.gca().xaxis.set_ticks_position('bottom')\n",
    "# set tick_line position of the bottom\n",
    "\n",
    "# turn on the left ticks for y-axis \n",
    "plt.gca().yaxis.set_ticks_position('left')\n",
    "# set tick_line position of the left\n",
    "\n",
    "#################################################\n",
    "\n",
    "\n",
    "\n",
    "## xlim \n",
    "plt.xlim(0, 4)\n",
    "plt.ylim(-3, 3)\n",
    "\n",
    "## xlabel\n",
    "plt.xlabel('x-axis')\n",
    "plt.ylabel('y-axis')\n",
    "\n",
    "\n",
    "## grid 刻度线\n",
    "plt.grid(color='r', linestyle=':')\n",
    "\n",
    "## axhline 水平参考线\n",
    "plt.axhline(y=0.5,\n",
    "\t\t\tcolor='r',\n",
    "\t\t\txmin=0.5,\n",
    "\t\t\txmax=1,\n",
    "\t\t\tlinestyle='--',\n",
    "\t\t\tlinewidth=2)\n",
    "'''\n",
    "xmin : scalar, optional, default: 0\n",
    "Should be between 0 and 1, 0 being the far left of the plot, 1 the far right of the plot.\n",
    "xmax : scalar, optional, default: 1\n",
    "Should be between 0 and 1, 0 being the far left of the plot, 1 the far right of the plot.\n",
    "'''\n",
    "plt.axvline(4, ymin=0.6,ymax=0.8,color='g',linestyle=\":\",linewidth=2)\n",
    "\n",
    "\n",
    "## axvspan 竖直参考区域\n",
    "plt.axvspan(xmin=1, # 起始位置\n",
    "\t\t\txmax=3,\t# 终止位置\n",
    "\t\t\tymin=0,\n",
    "\t\t\tymax=1,\n",
    "\t\t\tfacecolor='y', # 填充颜色\n",
    "\t\t\talpha=0.3) # 填充透明度\n",
    "\n",
    "plt.axhspan(ymin=0,ymax=1,xmin=0,xmax=1,facecolor='g',alpha=0.3)\n",
    "\n",
    "## annotate 指向型文本注释\n",
    "plt.annotate(s='maximum', # 注释文本\n",
    "\t\t\txy=(np.pi/2, 1.0), # 被注释图像内容的位置坐标 （箭头指向的地方，即需要标注的坐标点）\n",
    "\t\t\txytext=((np.pi/2)+1.0, 0.8), # 注释文本的位置坐标（箭头开始指的地方，即放置注释文本的地方）\n",
    "\t\t\tcolor='b',\t# 注释文本的颜色\n",
    "\t\t\tarrowprops=dict(arrowstyle='->', connectionstyle='arc3',color='b')) # 箭头的属性字典\n",
    "\n",
    "## text 无指向性文本注释\n",
    "\n",
    "plt.title('y=sin(x)')\n",
    "plt.text(x=np.pi, y=0.0, s='y=sin(x)', weight='bold', color='b')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
